Topic structure modeling

Authors:
David A. Evans;James G. Shanahan;Victor Sheftel
Affiliations:
Clairvoyance Corporation, Pittsburgh PA;Clairvoyance Corporation, Pittsburgh PA;Clairvoyance Corporation, Pittsburgh PA
Venue:
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2002

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Abstract

In this paper, we present a method based on document probes to quantify and diagnose topic structure, distinguishing topics as monolithic, structured, or diffuse. The method also yields a structure analysis that can be used directly to optimize filter (classifier) creation. Preliminary results illustrate the predictive value of the approach on TREC/Reuters-96 topics.