Using shortest path algorithms to identify criminal associations

Authors:
Jennifer Jie Xu;Hsinchun Chen
Affiliations:
The University of Arizona, Tucson, AZ;The University of Arizona, Tucson, AZ
Venue:
dg.o '02 Proceedings of the 2002 annual national conference on Digital government research
Year:
2002

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Abstract

Frequently in criminal investigations, law enforcement agencies face the problem of identifying associations between a group of entities such as individuals and organizations. In this paper we present a link analysis technique to solve such a problem. This approach uses shortest path algorithms to find the strongest associations between two or more given entities. The experimental results have demonstrated that our approach is potentially useful in terms of quality and efficiency. Specifically, we found that the two-tree Priority-First Search algorithm in most cases was the fastest algorithm to find shortest paths and the paths found consisted of meaningful criminal associations around 80 percent of the time.