A relevance feedback mechanism for cluster-based retrieval

被引:6
作者
Rooney, N [1 ]
Patterson, D
Galushka, M
Dobrynin, V
机构
[1] Univ Ulster, No Ireland Knowledge Engn Lab, Newtownabbey BT37 0QB, North Ireland
[2] St Petersburg State Univ, Fac Appl Math & Control Proc, St Petersburg 198504, Russia
关键词
information retrieval; document clustering; relevance feedback;
D O I
10.1016/j.ipm.2006.01.009
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1176 / 1184
页数:9
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