Research output: Contribution to journal › Article › peer-review
Contextual document clustering is a novel approach which uses information theoretic measures to cluster semantically related documents bound together by an implicit set of concepts or themes of narrow specificity. It facilitates cluster-based retrieval by assessing the similarity between a query and the cluster themes' probability distribution. In this paper, we assess a relevance feedback mechanism, based on query refinement, that modifies the query's probability distribution using a small number of documents that have been judged relevant to the query. We demonstrate that by providing only one relevance judgment, a performance improvement of 33% was obtained.
Original language | English |
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Pages (from-to) | 1176-1184 |
Number of pages | 9 |
Journal | Information Processing and Management |
Volume | 42 |
Issue number | 5 |
DOIs | |
State | Published - 1 Sep 2006 |
ID: 36369108