AAAI Publications, Workshops at the Twenty-Seventh AAAI Conference on Artificial Intelligence

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Detecting Patterns of Crime with Series Finder
Tong Wang, Cynthia Rudin, Daniel Wagner, Rich Sevieri

Last modified: 2013-06-29

Abstract


Many crimes can happen every day in a major city, and figuring out which ones are committed by the same individual or group is an important and difficult data mining challenge. To do this, we propose a pattern detection algorithm called Series Finder, that grows a pattern of discovered crimes from within a database, starting from a “seed” of a few crimes. Series Finder incorporates both the common characteristics of all patterns and the unique aspects of each specific pattern. We compared Series Finder with classic clustering and classification models applied to crime analysis. It has promising results on a decade’s worth of crime pattern data from the Cambridge Police Department.

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