A Recommendation Engine to Aid in Identifying Crime Patterns
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DOI: 10.1287/inte.2019.0985
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References listed on IDEAS
- Michael D. Porter, 2016. "A Statistical Approach to Crime Linkage," The American Statistician, Taylor & Francis Journals, vol. 70(2), pages 152-165, May.
- E. S. Levine & Jessica Tisch & Anthony Tasso & Michael Joy, 2017. "The New York City Police Department’s Domain Awareness System," Interfaces, INFORMS, vol. 47(1), pages 70-84, February.
- Linda V. Green & Peter J. Kolesar, 2004. "ANNIVERSARY ARTICLE: Improving Emergency Responsiveness with Management Science," Management Science, INFORMS, vol. 50(8), pages 1001-1014, August.
- G. O. Mohler & M. B. Short & Sean Malinowski & Mark Johnson & G. E. Tita & Andrea L. Bertozzi & P. J. Brantingham, 2015. "Randomized Controlled Field Trials of Predictive Policing," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1399-1411, December.
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- Justin J. Boutilier & Timothy C. Y. Chan, 2023. "Introducing and Integrating Machine Learning in an Operations Research Curriculum: An Application-Driven Course," INFORMS Transactions on Education, INFORMS, vol. 23(2), pages 64-83, January.
- Wheeler, Andrew Palmer & Steenbeek, Wouter, 2020. "Mapping the risk terrain for crime using machine learning," SocArXiv xc538, Center for Open Science.
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Keywords
law enforcement; pattern recognition; machine learning; decision support;All these keywords.
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