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An outlier-based data association method for linking criminal incidents [An article from: Decision Support Systems]

Author S. Lin, D.E. Brown
Publisher Elsevier
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Book Details
PublisherElsevier
ISBN / ASINB000RR534E
ISBN-13978B000RR5342
AvailabilityAvailable for download now
Sales Rank12,958,470
MarketplaceUnited States 🇺🇸

Description

This digital document is a journal article from Decision Support Systems, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Serial criminals are a major threat in the modern society. Associating incidents committed by the same offender is of great importance in studying serial criminals. In this paper, we present a new outlier-based approach to resolve this criminal incident association problem. In this approach, criminal incident data are first modeled into a number of cells, and then a measurement function, called outlier score function, is defined over these cells. Incidents in a cell are determined to be associated with each other when the score is significant enough. We applied our approach to a robbery dataset from Richmond, VA. Results show that this method can effectively solve the criminal incident association problem.