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Detecting patterns of crime with Series Finder

Publication ,  Conference
Wang, T; Rudin, C; Wagner, D; Sevieri, R
Published in: AAAI Workshop - Technical Report
January 1, 2013

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 Scholars

Published In

AAAI Workshop - Technical Report

ISBN

9781577356288

Publication Date

January 1, 2013

Volume

WS-13-17

Start / End Page

140 / 142
 

Citation

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MLA
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Wang, T., Rudin, C., Wagner, D., & Sevieri, R. (2013). Detecting patterns of crime with Series Finder. In AAAI Workshop - Technical Report (Vol. WS-13-17, pp. 140–142).
Wang, T., C. Rudin, D. Wagner, and R. Sevieri. “Detecting patterns of crime with Series Finder.” In AAAI Workshop - Technical Report, WS-13-17:140–42, 2013.
Wang T, Rudin C, Wagner D, Sevieri R. Detecting patterns of crime with Series Finder. In: AAAI Workshop - Technical Report. 2013. p. 140–2.
Wang, T., et al. “Detecting patterns of crime with Series Finder.” AAAI Workshop - Technical Report, vol. WS-13-17, 2013, pp. 140–42.
Wang T, Rudin C, Wagner D, Sevieri R. Detecting patterns of crime with Series Finder. AAAI Workshop - Technical Report. 2013. p. 140–142.

Published In

AAAI Workshop - Technical Report

ISBN

9781577356288

Publication Date

January 1, 2013

Volume

WS-13-17

Start / End Page

140 / 142