A data-driven software tool for enabling cooperative information sharing among police departments

A data-driven software tool for enabling cooperative information sharing among police departments

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Article ID: iaor20031979
Country: Netherlands
Volume: 141
Issue: 3
Start Page Number: 660
End Page Number: 678
Publication Date: Sep 2002
Journal: European Journal of Operational Research
Authors: ,
Keywords: artificial intelligence
Abstract:

Police departments utilize information technology for combating crime, however, mostly for tactical purposes. This paper presents an Artificial-Intelligence software, Crime Similarity System (CSS), that helps police departments develop a strategic viewpoint toward decision-making. CSS utilizes socioeconomic, crime and enforcement profiles of cities to generate a list of communities that are best candidates to cooperate and share experiences. By providing a list of relevant similar communities from whom past experience and learnings can be shared, this tool offers the potential for proactive management. CSS provides a user-friendly front-end enabling easy usage. Camden, NJ and Philadelphia, PA police departments were partners in this development effort. Feedback from these two police departments has validated the benefit of this software in uncovering opportunities for police departments to cooperate. An evaluation using human subjects showed that the CSS software provided significantly better support than a conventional database. The modeling framework developed in this work is versatile, potentially useful for applications beyond law enforcement.

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