An Outlier-based Data Association Method for Linking Criminal Incidents

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. D 2004 Published by Elsevier B.V.

• Type: Conference
• Year: 2003
• Where: SDM
• Authors: Song Lin, Donald E. Brown
• Keywords: Criminal Incident, Criminal Incident Association, Data Mining, Incident Association Problem, SDM 2003