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Semantic Query Expansion Combining Association Rules with Ontologies and Information Retrieval Techniques

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Data Warehousing and Knowledge Discovery (DaWaK 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3589))

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Abstract

Query expansion techniques are used to find the desired set of query terms to improve retrieval performance. One of the limitations with the query expansion techniques is that a query is often expanded only by the linguistic features of terms. This paper presents a novel semantic query expansion technique that combines association rules with ontologies and information retrieval techniques. We propose to use the association rule discovery to find good candidate terms to improve the retrieval performance. These candidate terms are automatically derived from collections and added to the original query. Our method is differentiated from others in that 1) it utilizes the semantics as well as linguistic properties of unstructured text corpus and 2) it makes use of contextual properties of important terms discovered by association rules. Experiments conducted on a subset of TREC collections give quite encouraging results. We achieve from 15.49% to 20.98% improvement in term of P@20 with TREC5 ad hoc queries.

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Author information

Authors and Affiliations

  1. College of Information Science & Technology, Drexel University, Philadelphia, PA, 19104

    Min Song, Il-Yeol Song, Xiaohua Hu & Robert Allen

Authors
  1. Min Song
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  2. Il-Yeol Song
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  3. Xiaohua Hu
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  4. Robert Allen
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Editor information

Editors and Affiliations

  1. Institute of Software Technology and Interactive Systems, Vienna University of Technology, Favoritenstr. 9-11/188, A-1040, Wien, Austria

    A Min Tjoa

  2. Department of Software and Computing Systems, University of Alicante, Spain

    Juan Trujillo

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© 2005 Springer-Verlag Berlin Heidelberg

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Song, M., Song, IY., Hu, X., Allen, R. (2005). Semantic Query Expansion Combining Association Rules with Ontologies and Information Retrieval Techniques. In: Tjoa, A.M., Trujillo, J. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2005. Lecture Notes in Computer Science, vol 3589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546849_32

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  • DOI: https://doi.org/10.1007/11546849_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28558-8

  • Online ISBN: 978-3-540-31732-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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