An empirical study of query expansion and cluster-based retrieval in language modeling approach

Authors:
Seung-Hoon Na;In-Su Kang;Ji-Eun Roh;Jong-Hyeok Lee
Affiliations:
Division of Electrical and Computer Engineering, POSTECH (Pohang University of Science and Technology), Namgu, Pohang, Republic of Korea;Division of Electrical and Computer Engineering, POSTECH (Pohang University of Science and Technology), Namgu, Pohang, Republic of Korea;Division of Electrical and Computer Engineering, POSTECH (Pohang University of Science and Technology), Namgu, Pohang, Republic of Korea;Division of Electrical and Computer Engineering, POSTECH (Pohang University of Science and Technology), Namgu, Pohang, Republic of Korea
Venue:
Information Processing and Management: an International Journal - Special issue: AIRS2005: Information retrieval research in Asia
Year:
2007

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Abstract

The term mismatch problem in information retrieval is a critical problem, and several techniques have been developed, such as query expansion, cluster-based retrieval and dimensionality reduction to resolve this issue. Of these techniques, this paper performs an empirical study on query expansion and cluster-based retrieval. We examine the effect of using parsimony in query expansion and the effect of clustering algorithms in cluster-based retrieval. In addition, query expansion and cluster-based retrieval are compared, and their combinations are evaluated in terms of retrieval performance by performing experimentations on seven test collections of NTCIR and TREC.