Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
553960 | Decision Support Systems | 2006 | 12 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Information Systems
Authors
Song Lin, Donald E. Brown,