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

来源：

INFORMATION PROCESSING & MANAGEMENT | 2006年 / 42卷 / 05期

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

页码：1176 / 1184

页数：9

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