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Crime Prediction Using Machine Learning and Deep Learning: A Systematic Review and Future Directions
Published 28 Mar 2023 in cs.LG, cs.AI, cs.CV, cs.CY, and cs.DB | (2303.16310v1)
Abstract: Predicting crime using machine learning and deep learning techniques has gained considerable attention from researchers in recent years, focusing on identifying patterns and trends in crime occurrences. This review paper examines over 150 articles to explore the various machine learning and deep learning algorithms applied to predict crime. The study provides access to the datasets used for crime prediction by researchers and analyzes prominent approaches applied in machine learning and deep learning algorithms to predict crime, offering insights into different trends and factors related to criminal activities. Additionally, the paper highlights potential gaps and future directions that can enhance the accuracy of crime prediction. Finally, the comprehensive overview of research discussed in this paper on crime prediction using machine learning and deep learning approaches serves as a valuable reference for researchers in this field. By gaining a deeper understanding of crime prediction techniques, law enforcement agencies can develop strategies to prevent and respond to criminal activities more effectively.
- Crime forecasting: a machine learning and computer vision approach to crime prediction and prevention. Visual Computing for Industry, Biomedicine, and Art 4, 1–14 (2021) . (2) Chun, S. A. et al. Crime prediction model using deep neural networks, 512–514 (2019). (3) Kshatri, S. S. et al. An empirical analysis of machine learning algorithms for crime prediction using stacked generalization: An ensemble approach. IEEE Access 9, 67488–67500 (2021) . (4) Janiesch, C., Zschech, P. & Heinrich, K. Machine learning and deep learning. Electronic Markets 31 (3), 685–695 (2021) . (5) Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chun, S. A. et al. Crime prediction model using deep neural networks, 512–514 (2019). (3) Kshatri, S. S. et al. An empirical analysis of machine learning algorithms for crime prediction using stacked generalization: An ensemble approach. IEEE Access 9, 67488–67500 (2021) . (4) Janiesch, C., Zschech, P. & Heinrich, K. Machine learning and deep learning. Electronic Markets 31 (3), 685–695 (2021) . (5) Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kshatri, S. S. et al. An empirical analysis of machine learning algorithms for crime prediction using stacked generalization: An ensemble approach. IEEE Access 9, 67488–67500 (2021) . (4) Janiesch, C., Zschech, P. & Heinrich, K. Machine learning and deep learning. Electronic Markets 31 (3), 685–695 (2021) . (5) Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Janiesch, C., Zschech, P. & Heinrich, K. Machine learning and deep learning. Electronic Markets 31 (3), 685–695 (2021) . (5) Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. 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(57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Chun, S. A. et al. Crime prediction model using deep neural networks, 512–514 (2019). (3) Kshatri, S. S. et al. An empirical analysis of machine learning algorithms for crime prediction using stacked generalization: An ensemble approach. IEEE Access 9, 67488–67500 (2021) . (4) Janiesch, C., Zschech, P. & Heinrich, K. Machine learning and deep learning. Electronic Markets 31 (3), 685–695 (2021) . (5) Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kshatri, S. S. et al. An empirical analysis of machine learning algorithms for crime prediction using stacked generalization: An ensemble approach. IEEE Access 9, 67488–67500 (2021) . (4) Janiesch, C., Zschech, P. & Heinrich, K. Machine learning and deep learning. Electronic Markets 31 (3), 685–695 (2021) . (5) Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Janiesch, C., Zschech, P. & Heinrich, K. Machine learning and deep learning. Electronic Markets 31 (3), 685–695 (2021) . (5) Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. 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Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Janiesch, C., Zschech, P. & Heinrich, K. Machine learning and deep learning. Electronic Markets 31 (3), 685–695 (2021) . (5) Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. 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Forensic Science International: Digital Investigation 39, 301273 (2021) .
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Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Raza, D. M. & Victor, D. B. Data mining and region prediction based on crime using random forest, 980–987 (IEEE, 2021). (6) Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. 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Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Elluri, L., Mandalapu, V. & Roy, N. Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Developing machine learning based predictive models for smart policing, 198–204 (IEEE, 2019). (7) Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Meijer, A. & Wessels, M. Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration 42 (12), 1031–1039 (2019) . (8) Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hossain, S., Abtahee, A., Kashem, I., Hoque, M. M. & Sarker, I. H. Crime prediction using spatio-temporal data, 277–289 (Springer, 2020). (9) Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . 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Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. 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Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). 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(15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Saraiva, M., Matijošaitienė, I., Mishra, S. & Amante, A. Crime prediction and monitoring in porto, portugal, using machine learning, spatial and text analytics. ISPRS International Journal of Geo-Information 11 (7), 400 (2022) . (10) Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
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(16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kounadi, O., Ristea, A., Araujo, A. & Leitner, M. A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- A systematic review on spatial crime forecasting. Crime science 9, 1–22 (2020) . (11) Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Morrisey, L. J. in Bibliometric and bibliographic analysis in an era of electronic scholarly communication 149–160 (Routledge, 2013). (12) Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. 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Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Hofmann, M. & Chisholm, A. Text mining and visualization: Case studies using open-source tools Vol. 40 (CRC Press, 2016). (13) Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. 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Forensic Science International: Digital Investigation 39, 301273 (2021) .
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Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tamilarasi, P. & Rani, R. U. Diagnosis of crime rate against women using k-fold cross validation through machine learning, 1034–1038 (IEEE, 2020). (14) Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . 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(38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kumar, A., Verma, A., Shinde, G., Sukhdeve, Y. & Lal, N. Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Crime prediction using k-nearest neighboring algorithm, 1–4 (IEEE, 2020). (15) Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Agarwal, S., Yadav, L. & Thakur, M. K. Crime prediction based on statistical models, 1–3 (IEEE, 2018). (16) Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Bandekar, S. R. & Vijayalakshmi, C. Design and analysis of machine learning algorithms for the reduction of crime rates in india. Procedia Computer Science 172, 122–127 (2020) . (17) Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. 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(29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sangani, A., Sampat, C. & Pinjarkar, V. Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. 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(54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
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(18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. 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Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Crime prediction and analysis (2019). (18) Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sivanagaleela, B. & Rajesh, S. Crime analysis and prediction using fuzzy c-means algorithm, 595–599 (IEEE, 2019). (19) Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
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(59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shermila, A. M., Bellarmine, A. B. & Santiago, N. Crime data analysis and prediction of perpetrator identity using machine learning approach, 107–114 (IEEE, 2018). (20) Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
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Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Kim, S., Joshi, P., Kalsi, P. S. & Taheri, P. Crime analysis through machine learning, 415–420 (IEEE, 2018). (21) Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. 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Forensic Science International: Digital Investigation 39, 301273 (2021) .
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Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- A data-driven approach for spatio-temporal crime predictions in smart cities, 17–24 (IEEE, 2018). (22) Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Catlett, C., Cesario, E., Talia, D. & Vinci, A. Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing 53, 62–74 (2019) . (23) Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yi, F., Yu, Z., Zhuang, F., Zhang, X. & Xiong, H. An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. 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(57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- An integrated model for crime prediction using temporal and spatial factors, 1386–1391 (IEEE, 2018). (24) Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Dash, S. K., Safro, I. & Srinivasamurthy, R. S. Spatio-temporal prediction of crimes using network analytic approach, 1912–1917 (IEEE, 2018). (25) Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
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Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Han, X., Hu, X., Wu, H., Shen, B. & Wu, J. Risk prediction of theft crimes in urban communities: an integrated model of lstm and st-gcn. IEEE Access 8, 217222–217230 (2020) . (26) Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Li, Z., Huang, C., Xia, L., Xu, Y. & Pei, J. Spatial-temporal hypergraph self-supervised learning for crime prediction, 2984–2996 (IEEE, 2022). (27) Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). 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(35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Tasnim, N., Imam, I. T. & Hashem, M. A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . 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Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
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Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model. IEEE Access 10, 48009–48030 (2022) . (28) Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, B. et al. Unsupervised domain adaptation for crime risk prediction across cities. IEEE Transactions on Computational Social Systems (2022) . (29) Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Butt, U. M. et al. Spatio-temporal crime predictions by leveraging artificial intelligence for citizens security in smart cities. IEEE Access 9, 47516–47529 (2021) . (30) Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. 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A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. 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(41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yao, S. et al. Prediction of crime hotspots based on spatial factors of random forest, 811–815 (IEEE, 2020). (31) Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. 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(57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. 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Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sathiyanarayanan, M., Junejo, A. K. & Fadahunsi, O. Visual analysis of predictive policing to improve crime investigation, 197–203 (IEEE, 2019). (32) Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Araújo, A., Cacho, N., Bezerra, L., Vieira, C. & Borges, J. Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
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Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Towards a crime hotspot detection framework for patrol planning, 1256–1263 (IEEE, 2018). (33) Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Almuhanna, A. A., Alrehili, M. M., Alsubhi, S. H. & Syed, L. Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Prediction of crime in neighbourhoods of new york city using spatial data analysis, 23–30 (IEEE, 2021). (34) Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Baqir, A., ul Rehman, S., Malik, S., ul Mustafa, F. & Ahmad, U. Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Evaluating the performance of hierarchical clustering algorithms to detect spatio-temporal crime hot-spots, 1–5 (IEEE, 2020). (35) Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Algefes, A., Aldossari, N., Masmoudi, F. & Kariri, E. A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- A text-mining approach for crime tweets in saudi arabia: from analysis to prediction, 109–114 (IEEE, 2022). (36) Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sandagiri, S., Kumara, B. & Kuhaneswaran, B. Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. 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(57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Detecting crime related twitter posts using artificial neural networks based approach, 5–10 (IEEE, 2020). (37) Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Permana, M. A., Thohir, M. I., Mantoro, T. & Ayu, M. A. Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Crime rate detection based on text mining on social media using logistic regression algorithm, 1–6 (IEEE, 2021). (38) Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhou, X., Wang, X., Brown, G., Wang, C. & Chin, P. Mixed spatio-temporal neural networks on real-time prediction of crimes, 1749–1754 (IEEE, 2021). (39) Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. 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(51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. 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Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. 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Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. 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(54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). 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Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). 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Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. 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Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Shenoy, R., Yadav, D., Lakhotiya, H. & Sisodia, J. An intelligent framework for crime prediction using behavioural tracking and motion analysis, 1–6 (IEEE, 2022). (40) Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. 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Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). 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Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. 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Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. 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(62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. 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(51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Aldossari, N., Algefes, A., Masmoudi, F. & Kariri, E. Data science approach for crime analysis and prediction: Saudi arabia use-case, 20–25 (IEEE, 2022). (41) Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. 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(57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ma, Y., Nakamura, K., Lee, E.-J. & Bhattacharyya, S. S. Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Eadtc: An approach to interpretable and accurate crime prediction, 170–177 (IEEE, 2022). (42) Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. 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Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Boukabous, M. & Azizi, M. Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Multimodal sentiment analysis using audio and text for crime detection, 1–5 (IEEE, 2022). (43) Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Alves, L. G., Ribeiro, H. V. & Rodrigues, F. A. Crime prediction through urban metrics and statistical learning. Physica A: Statistical Mechanics and its Applications 505, 435–443 (2018) . (44) He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
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(49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . He, J. & Zheng, H. Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Prediction of crime rate in urban neighborhoods based on machine learning. Engineering Applications of Artificial Intelligence 106, 104460 (2021) . (45) ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . ToppiReddy, H. K. R., Saini, B. & Mahajan, G. Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Crime prediction & monitoring framework based on spatial analysis. Procedia computer science 132, 696–705 (2018) . (46) Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Wolf, A. et al. Prediction of violent crime on discharge from secure psychiatric hospitals: A clinical prediction rule (fovox). European psychiatry 47, 88–93 (2018) . (47) Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Sahay, K. B. et al. A real time crime scene intelligent video surveillance systems in violence detection framework using deep learning techniques. Computers and Electrical Engineering 103, 108319 (2022) . (48) Utomo, P. E. P. et al. Prediction the crime motorcycles of theft using arimax-tfm with single input, 1–7 (IEEE, 2018). (49) Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Utomo, P. E. P. et al. 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Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Ingilevich, V. & Ivanov, S. Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
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Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. 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(54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Crime rate prediction in the urban environment using social factors. Procedia Computer Science 136, 472–478 (2018) . (50) da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . da Silva, A. R. C., de Paula Júnior, I. C., da Silva, T. L. C., de Macêdo, J. A. F. & Silva, W. C. P. Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Prediction of crime location in a brazilian city using regression techniques, 331–336 (IEEE, 2020). (51) Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, P., Das, A. K., Nayak, J., Pelusi, D. & Ding, W. Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Incremental classifier in crime prediction using bi-objective particle swarm optimization. Information Sciences 562, 279–303 (2021) . (52) Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yan, Z., Chen, H., Dong, X., Zhou, K. & Xu, Z. Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on xgboost. Expert Systems with Applications 207, 117943 (2022) . (53) Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Zhang, X. et al. Interpretable machine learning models for crime prediction. 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Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Zhang, X. et al. Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems 94, 101789 (2022) . (54) Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Trinhammer, M., Merrild, A. H., Lotz, J. & Makransky, G. Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Predicting crime during or after psychiatric care: Evaluating machine learning for risk assessment using the danish patient registries. Journal of psychiatric research 152, 194–200 (2022) . (55) Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Das, A. K. & Das, P. Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Graph based ensemble classification for crime report prediction. Applied Soft Computing 125, 109215 (2022) . (56) Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Liang, W., Wang, Y., Tao, H. & Cao, J. Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion. Neurocomputing 486, 286–297 (2022) . (57) Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Navalgund, U. V. & Priyadharshini, K. Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Crime intention detection system using deep learning, 1–6 (IEEE, 2018). (58) Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Nakib, M., Khan, R. T., Hasan, M. S. & Uddin, J. Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Crime scene prediction by detecting threatening objects using convolutional neural network, 1–4 (IEEE, 2018). (59) Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Chackravarthy, S., Schmitt, S. & Yang, L. Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Intelligent crime anomaly detection in smart cities using deep learning, 399–404 (IEEE, 2018). (60) Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Yadav, R. & Sheoran, S. K. Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Crime prediction using auto regression techniques for time series data, 1–5 (IEEE, 2018). (61) Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Wang, H. & Ma, S. Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Preventing crimes against public health with artificial intelligence and machine learning capabilities. Socio-Economic Planning Sciences 80, 101043 (2022) . (62) Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) . Abraham, J., Ng, R., Morelato, M., Tahtouh, M. & Roux, C. Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
- Automatically classifying crime scene images using machine learning methodologies. Forensic Science International: Digital Investigation 39, 301273 (2021) .
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