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Data merging: Theory of Evidence vs knowledge-bases merging operators

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Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2143))

Abstract

This paper addresses the problem of merging data provided by several sources of information. It aims at comparing two techniques of merging, one provided by Theory of Evidence and the other provided in the field of logic for merging knowledge-bases.

For doing so, it first presents a logical interpretation of Theory of Evidence, which is proved to be valid when the numbers are rational. Then, it shows the equivalence between the Maximum of Plausibility Decision Strategy of Theory of Evidence and a particular knowldege-bases merging operator, known to be a majority and also an arbitration operator.

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Author information

Authors and Affiliations

  1. ONERA Centre de Toulouse, 2 av Ed. Belin, 31055, Toulouse, France

    Laurence Cholvy

Authors
  1. Laurence Cholvy
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Editor information

Editors and Affiliations

  1. Université Paul Sabatier, IRIT-CNRS, 118 route de Narbonne, 31062, Toulouse Cedex 4, France

    Salem Benferhat  & Philippe Besnard  & 

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© 2001 Springer-Verlag Berlin Heidelberg

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Cholvy, L. (2001). Data merging: Theory of Evidence vs knowledge-bases merging operators. In: Benferhat, S., Besnard, P. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2001. Lecture Notes in Computer Science(), vol 2143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44652-4_42

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  • DOI: https://doi.org/10.1007/3-540-44652-4_42

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42464-2

  • Online ISBN: 978-3-540-44652-1

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