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Belief Merging-Based Case Combination

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Case-Based Reasoning Research and Development (ICCBR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5650))

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Abstract

Integrity constraint belief merging aims at producing from several knowledge bases, that may be mutually inconsistent, a synthetic knowledge base satisfying a given integrity constraint. It is applied here to case combination for case-based reasoning. This approach is shown to extend Eyke Hüllermeier’s credible case-based inference and to be reducible under some assumptions to linear programming.

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Author information

Authors and Affiliations

  1. Orpailleur, LORIA, CNRS, INRIA, Nancy University, BP 239, 54506, Vandœuvre-lès-Nancy

    Julien Cojan & Jean Lieber

Authors
  1. Julien Cojan
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  2. Jean Lieber
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Editor information

Editors and Affiliations

  1. Adaptive Information Cluster, School of Computer Science & Informatics, University College Dublin,, Computer Science Building, Belfield, Dublin 4, Ireland

    Lorraine McGinty

  2. Department of Software and Information Systems, College of Computing and Informatics, University of North Carolina at Charlotte, 9201 University City Boulevard, NC 28223-0001, Charlotte, USA

    David C. Wilson

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© 2009 Springer-Verlag Berlin Heidelberg

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Cojan, J., Lieber, J. (2009). Belief Merging-Based Case Combination. In: McGinty, L., Wilson, D.C. (eds) Case-Based Reasoning Research and Development. ICCBR 2009. Lecture Notes in Computer Science(), vol 5650. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02998-1_9

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  • DOI: https://doi.org/10.1007/978-3-642-02998-1_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02997-4

  • Online ISBN: 978-3-642-02998-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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