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Lexical Entailment for Information Retrieval

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Advances in Information Retrieval (ECIR 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3936))

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Abstract

Textual Entailment has recently been proposed as an application independent task of recognising whether the meaning of one text may be inferred from another. This is potentially a key task in many NLP applications. In this contribution, we investigate the use of various lexical entailment models in Information Retrieval, using the language modelling framework. We show that lexical entailment potentially provides a significant boost in performance, similar to pseudo-relevance feedback, but at a lower computational cost. In addition, we show that the performance is relatively stable with respect to the corpus the lexical entailment measure is estimated on.

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Author information

Authors and Affiliations

  1. Xerox Research Centre Europe, 6, chemin de Maupertuis, F-38240, Meylan, France

    Stéphane Clinchant, Cyril Goutte & Eric Gaussier

Authors
  1. Stéphane Clinchant
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  2. Cyril Goutte
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  3. Eric Gaussier
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Editor information

Editors and Affiliations

  1. Queen Mary, University of London, London, UK

    Mounia Lalmas

  2. Department of Information Science, City University, Northampton Square, EC1V OHB, London, UK

    Andy MacFarlane

  3. Knowledge Media Institute, The Open University, MK7 6AA, Milton Keynes, UK

    Stefan Rüger

  4. Queen Mary University of London, UK

    Anastasios Tombros

  5. CWI, Amsterdam, The Netherlands

    Theodora Tsikrika

  6. Department of Computing, Imperial College London, South Kensington Campus, SW7 2AZ, London, UK

    Alexei Yavlinsky

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© 2006 Springer-Verlag Berlin Heidelberg

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Clinchant, S., Goutte, C., Gaussier, E. (2006). Lexical Entailment for Information Retrieval. In: Lalmas, M., MacFarlane, A., Rüger, S., Tombros, A., Tsikrika, T., Yavlinsky, A. (eds) Advances in Information Retrieval. ECIR 2006. Lecture Notes in Computer Science, vol 3936. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11735106_20

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  • DOI: https://doi.org/10.1007/11735106_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33347-0

  • Online ISBN: 978-3-540-33348-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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