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Workshop on Distributed Information Retrieval

DIR 2003: Distributed Multimedia Information Retrieval pp 43–57Cite as

Decision-Theoretic Resource Selection for Different Data Types in MIND

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2924))

Abstract

In a federated digital library system, it is too expensive to query every accessible library. Resource selection is the task to decide to which libraries a query should be routed. In this paper, we describe a novel technique that is used in the MIND project. Our approach, decision-theoretic framework (DTF), differs from existing algorithms like CORI in two ways: It computes a selection which minimises the overall costs (e.g. retrieval quality, time, money) of the distributed retrieval. And it allows for other data types beside text (e.g., names, years, images), whereas other resource selection techniques are restricted to text.

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Author information

Authors and Affiliations

  1. Institute of Informatics and Interactive Systems, University of Duisburg-Essen, 47048, Duisburg, Germany

    Henrik Nottelmann & Norbert Fuhr

Authors
  1. Henrik Nottelmann
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  2. Norbert Fuhr
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Editor information

Editors and Affiliations

  1. Language Technologies Institute, Carnegie Mellon University, 5000 Forbes Ave, 15213, Pittsburgh, PA, USA

    Jamie Callan

  2. Department of Computer and Information Science, University of Strathclyde, Scotland

    Fabio Crestani

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

    Mark Sanderson

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© 2004 Springer-Verlag Berlin Heidelberg

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Nottelmann, H., Fuhr, N. (2004). Decision-Theoretic Resource Selection for Different Data Types in MIND. In: Callan, J., Crestani, F., Sanderson, M. (eds) Distributed Multimedia Information Retrieval. DIR 2003. Lecture Notes in Computer Science, vol 2924. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24610-7_4

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  • DOI: https://doi.org/10.1007/978-3-540-24610-7_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20875-4

  • Online ISBN: 978-3-540-24610-7

  • eBook Packages: Springer Book Archive

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