Combining Logic and Probabilities for Discovering Mappings between Taxonomies

  • Rémi Tournaire
  • Jean-Marc Petit
  • Marie-Christine Rousset
  • Alexandre Termier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6291)


In this paper, we investigate a principled approach for defining and discovering probabilistic mappings between two taxonomies. First, we compare two ways of modeling probabilistic mappings which are compatible with the logical constraints declared in each taxonomy. Then we describe a generate and test algorithm which minimizes the number of calls to the probability estimator for determining those mappings whose probability exceeds a certain threshold. Finally, we provide an experimental analysis of this approach.


Schema Match Ontology Match Inclusion Statement Logical Semantic XXth Century 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Rémi Tournaire
    • 1
  • Jean-Marc Petit
    • 2
  • Marie-Christine Rousset
    • 1
  • Alexandre Termier
    • 1
  1. 1.Laboratory of Informatics of Grenoble UMR 5217University of GrenobleSt-Martin d’Hères CedexFrance
  2. 2.INSA Lyon, LIRIS UMR 5205Villeurbanne CedexFrance

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