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              <text>Crime Patterns; Crime prevention; Detection; Machine Learning; Prediction</text>
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              <text>Crime profoundly impacts individuals, communities, and families. Technological advancements have provided perpetrators with new opportunities for criminal activities. The primary objective of the police department is to resolve crimes, ensuring justice for the victims. Additionally, preventing such incidents is crucial for creating a safer world. The landscape of criminal justice has undergone a significant shift with the integration of machine learning techniques, unlocking unparalleled potential for accuracy and efficiency. This study thoroughly examines the concept of various applications of machine learning in crime detection, prediction, and prevention. We examine the evolution of these technologies, from early developments to state- of-the-art methodologies, conducting a thorough analysis of their strengths, limitations, and ethical considerations. Moreover, the paper sheds light on crimes discussed in academic circles, serving as a repository for scholars and researchers. This facilitates informed discussions and guides future research endeavours.  2024 IEEE.</text>
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              <text>Rachana N.; Norton Stanley S.A.; Sandeep J.; Sreeja C.S.</text>
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              <text>Proceedings of International Conference on Communication, Computer Sciences and Engineering, IC3SE 2024, pp. 68-74.</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>ISBN: 979-835036684-6</text>
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              <text>Rachana N., Christ (Deemed To Be University), Department Of Computer Science, Bangalore, India; Norton Stanley S.A., Christ (Deemed To Be University), Department Of Computer Science, Bangalore, India; Sandeep J., Christ (Deemed To Be University), Department Of Computer Science, Bangalore, India; Sreeja C.S., Christ (Deemed To Be University), Department Of Computer Science, Bangalore, India</text>
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