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Combining Web Document Representations in a Bayesian Inference Network Model Using Link and Content-Based Evidence

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Advances in Information Retrieval (ECIR 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2291))

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Abstract

This paper introduces an expressive formal Information Retrieval model developed for the Web. It is based on the Bayesian inference network model and views IR as an evidential reasoning process. It supports the explicit combination of multiple Web document representations under a single framework. Information extracted from the content of Web documents and derived from the analysis of the Web link structure is used as source of evidence in support of the ranking algorithm. This content and link-based evidential information is utilised in the generation of the multiple Web document representations used in the combination.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Queen Mary, University of London, Mile End Road, E1 4NS, London, UK

    Theodora Tsikrika & Mounia Lalmas

Authors
  1. Theodora Tsikrika
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  2. Mounia Lalmas
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Editor information

Editors and Affiliations

  1. Department of Computer and Information Sciences, University of Strathclyde, 26 Richmond Street, G1 1XH, Glasgow, UK

    Fabio Crestani

  2. School of Information and Communication Technologies, University of Paisley, High Street, PA1 2BE, Paisley, UK

    Mark Girolami

  3. Computing Science Department, University of Glasgow, 17 Lilybank Gardens, G12 8RZ, Glasgow, UK

    Cornelis Joost van Rijsbergen

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© 2002 Springer-Verlag Berlin Heidelberg

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Tsikrika, T., Lalmas, M. (2002). Combining Web Document Representations in a Bayesian Inference Network Model Using Link and Content-Based Evidence. In: Crestani, F., Girolami, M., van Rijsbergen, C.J. (eds) Advances in Information Retrieval. ECIR 2002. Lecture Notes in Computer Science, vol 2291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45886-7_4

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  • DOI: https://doi.org/10.1007/3-540-45886-7_4

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43343-9

  • Online ISBN: 978-3-540-45886-9

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