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Judging the Spatial Relevance of Documents for GIR

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

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Abstract

Geographic Information Retrieval (GIR) is concerned with the retrieval of documents based on both thematic and geographic content. An important issue in GIR, as for all IR, is relevance. In this paper we argue that spatial relevance should be considered independently from thematic relevance, and propose an initial scheme. A pilot study to assess this relevance scheme is presented, with initial results suggesting that users can distinguish between these two relevance dimensions, and that furthermore they have different properties. We suggest that spatial relevance requires greater assessor effort and more localised geographic knowledge than judging thematic relevance.

Research part-funded by EU-IST Projects IST-2001-35047 (SPIRIT) and IST-2002-2.3.1.12 (BRICKS).

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Author information

Authors and Affiliations

  1. Department of Information Studies, University of Sheffield, UK

    Paul D. Clough

  2. Department of Computer Science, University of Glasgow, UK

    Hideo Joho

  3. Department of Geography, University of Zurich, Switzerland

    Ross Purves

Authors
  1. Paul D. Clough

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  2. Hideo Joho

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  3. Ross Purves

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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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Clough, P.D., Joho, H., Purves, R. (2006). Judging the Spatial Relevance of Documents for GIR. 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_62

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