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Minimum Redundancy Cut in Ontologies for Semantic Indexing

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Progress in Artificial Intelligence (EPIA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3808))

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Abstract

This paper presents a new method that aims at improving semantic indexing while reducing the number of indexing terms. Indexing terms are determined using a minimum redundancy cut in a hierarchy of conceptual hypernyms provided by an ontology (e.g. WordNet, EDR). The results of some information retrieval experiments carried out on several standard document collections using the EDR ontology are presented, illustrating the benefit of the method.

This work was partially supported by the Swiss National Fund for Scientific Research (SNFSR) under grant #200020–103529.

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Author information

Authors and Affiliations

  1. School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Lausanne, Switzerland

    Florian Seydoux & Jean-Cédric Chappelier

Authors
  1. Florian Seydoux
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  2. Jean-Cédric Chappelier
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Editor information

Editors and Affiliations

  1. Portugal Telecom Inovação (PTI), Centro de Informatica e Sistemas da Universidade de Coimbra (CISUC),  

    Carlos Bento

  2. Department of Informatics Engineering, Coimbra University, Portugal

    Amílcar Cardoso

  3. Centre of Human Language Technology and Bioinformatics, University of Beira Interior, 6201-001, Covilhã, Portugal

    Gaël Dias

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© 2005 Springer-Verlag Berlin Heidelberg

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Seydoux, F., Chappelier, JC. (2005). Minimum Redundancy Cut in Ontologies for Semantic Indexing. In: Bento, C., Cardoso, A., Dias, G. (eds) Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science(), vol 3808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595014_64

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  • DOI: https://doi.org/10.1007/11595014_64

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30737-2

  • Online ISBN: 978-3-540-31646-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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