NDLI: Query Expansion based on Concept Clique for Markov Network Information Retrieval Model

Content Provider	IEEE Xplore Digital Library
Author	Lixin Gan Shengqian Wang Mingwen Wang Zhihua Xie Lin Zhang Zhenghua Shu
Copyright Year	2008
Description	Author affiliation: Key Lab. of Opt.-Electron. &Commun., Jiangxi Sci. & Technol. Normal Univ., Nanchang (Lixin Gan; Shengqian Wang)
Abstract	Query expansion is a common technique used to improve retrieval effectiveness. In this paper, we propose a novel query expansion technique based on concept clique for Markov network information retrieval model. This technique strengthens the simple relationships between terms in the following two ways:(1) terms in a clique express a similar concept and will be added into query expansion, so that it is effective to expanded into some terms with low similar to query terms but highly related to query topic; (2) query term dependencies are used to select concept cliques as candidates. The selection of concept cliques based on a connected graph is effective to avoid topic drift during expanding polysemous query terms. Experiments on several collections show that new approach makes significant improvements and more effective on collections with polysemous terms.
Starting Page	29
Ending Page	33
File Size	234792
Page Count	5
File Format	PDF
ISBN	9780769533056
DOI	10.1109/FSKD.2008.648
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge engineering Laboratories Optical computing Optical fiber networks Information retrieval Query expansion Thesauri Data mining Markov random fields concept clique Markov network Computer networks information connected graph Fuzzy systems
Content Type	Text
Resource Type	Article

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