Relevance feedback with a small number of relevance judgements: incremental relevance feedback vs. document clustering

Authors:
Makoto Iwayama
Affiliations:
Central Research Laboratory, Hitachi, Ltd., Hatoyama, Saitama 350-0395, Japan
Venue:
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2000

Citing 14
Cited 30

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Abstract

The use of incremental relevance feedback and document clustering were investigated in an relevance feedback environment in which the number of relevance judgements was quite small. Through experiments on the TREC collection, the incremental relevance feedback approach was found not to improve the overall search effectiveness. The clustering approach was found to be promising, although it sometimes over-focuses on a particular topic in a query and ignores the others. To overcome this problem, a query-biased clustering algorithm was developed and shown to be effective.