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Geographic and Textual Data Fusion in Forostar

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Evaluating Systems for Multilingual and Multimodal Information Access (CLEF 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5706))

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Abstract

In this paper we provide some analysis of data fusion techniques employed at GeoCLEF 2008 to merge textual and geographic relevance. These methods are compared to our own experiments, where using our GIR system, Forostar, we show that an aggressive filter-based data fusion method can outperform a more sophisticated penalisation method.

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Author information

Authors and Affiliations

  1. Department of Computing, Imperial College London, London, SW7 2AZ, UK

    Simon Overell & Stefan Rüger

  2. Knowledge Media Institute, The Open University Walton Hall, Milton Keynes, MK7 6AA, UK

    Adam Rae & Stefan Rüger

Authors
  1. Simon Overell
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  2. Adam Rae
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  3. Stefan Rüger
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Editor information

Editors and Affiliations

  1. Istituto di Scienza e Tecnologie dell’Informazione, CNR, Pisa, Italy

    Carol Peters

  2. RWTH Aachen University, Aachen, Germany

    Thomas Deselaers

  3. University of Padua, Padua, Italy

    Nicola Ferro

  4. LSI-UNED, Madrid, Spain

    Julio Gonzalo  & Anselmo Peñas  & 

  5. Dublin City University, Dublin 9, Ireland

    Gareth J. F. Jones

  6. Helsinki University of Technology, Espoo, Finland

    Mikko Kurimo

  7. University of Hildesheim, Hildesheim, Germany

    Thomas Mandl

  8. Humboldt University Berlin, Germany

    Vivien Petras

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Overell, S., Rae, A., Rüger, S. (2009). Geographic and Textual Data Fusion in Forostar. In: Peters, C., et al. Evaluating Systems for Multilingual and Multimodal Information Access. CLEF 2008. Lecture Notes in Computer Science, vol 5706. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04447-2_109

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  • DOI: https://doi.org/10.1007/978-3-642-04447-2_109

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04446-5

  • Online ISBN: 978-3-642-04447-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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