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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Badia, A., Kantardzic, M. (2005). Link Analysis Tools for Intelligence and Counterterrorism. In: Kantor, P., et al. Intelligence and Security Informatics. ISI 2005. Lecture Notes in Computer Science, vol 3495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427995_5
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DOI: https://doi.org/10.1007/11427995_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25999-2
Online ISBN: 978-3-540-32063-0
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