Link analysis tools for intelligence and counterterrorism

Authors:
Antonio Badia;Mehmed Kantardzic
Affiliations:
University of Louisville, Louisville, KY;University of Louisville, Louisville, KY
Venue:
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
Year:
2005

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Abstract

Association rule mining is an important data analysis tool that can be applied with success to a variety of domains. However, most association rule mining algorithms seek to discover statistically significant patterns (i.e. those with considerable support). We argue that, in law-enforcement, intelligence and counterterrorism work, sometimes it is necessary to look for patterns which do not have large support but are otherwise significant. Here we present some ideas on how to detect potentially interesting links that do not have strong support in a dataset. While deciding what is of interest must ultimately be done by a human analyst, our approach allows filtering some events with interesting characteristics among the many events with low support that may appear in a dataset.