Detection using clustering query results

Authors:
Nazli Goharian;Alana Platt
Affiliations:
Information Retrieval Laboratory, Computer Science Department, Illinois Institute of Technology;Information Retrieval Laboratory, Computer Science Department, Illinois Institute of Technology
Venue:
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
Year:
2006

Citing 1
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Abstract

Previously, we proposed techniques to detect the misuse of search systems using predominantly relevance feedback based techniques. Although the approaches developed achieved high detection rate, they did so with a relatively high rate of false alarm. We now present a clustering query results based approach. This approach supports a higher precision, i.e., lower false alarm rate, with only a modest compromise on detection rate, namely recall.