Detecting patterns of crime with Series Finder

Published

Conference Paper

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. Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved.

Duke Authors

Cited Authors

  • Wang, T; Rudin, C; Wagner, D; Sevieri, R

Published Date

  • January 1, 2013

Published In

  • Aaai Workshop Technical Report

Volume / Issue

  • WS-13-17 /

Start / End Page

  • 140 - 142

International Standard Book Number 13 (ISBN-13)

  • 9781577356288

Citation Source

  • Scopus