Discovery of probabilistic mappings between taxonomies: principles and experiments

  • Authors:
  • Rémi Tournaire;Jean-Marc Petit;Marie-Christine Rousset;Alexandre Termier

  • Affiliations:
  • Université de Grenoble, UJF/Grenoble INP/UPMF/CNRS, LIG UMR 5217, St-Martin d'Hères Cedex, France;Université de Lyon, CNRS, INSA-Lyon, LIRIS UMR 5205, Villeurbanne Cedex, France;Université de Grenoble, UJF/Grenoble INP/UPMF/CNRS, LIG UMR 5217, St-Martin d'Hères Cedex, France;Université de Grenoble, UJF/Grenoble INP/UPMF/CNRS, LIG UMR 5217, St-Martin d'Hères Cedex, France

  • Venue:
  • Journal on data semantics XV
  • Year:
  • 2011

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Abstract

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 whichminimizes 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.