Discovery of Probabilistic Mappings between Taxonomies: Principles and Experiments

Remi Tournaire 1, 2 Alexandre Termier 3 Jean-Marc Petit 1 Marie-Christine Rousset 3
1 BD - Base de Données
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 LIG - Laboratoire d'Informatique de Grenoble
3 LIG Laboratoire d'Informatique de Grenoble - HADAS
LIG - Laboratoire d'Informatique de Grenoble
Abstract : In this paper, we investigate a principled approach for de?ning 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.
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Conference papers
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https://hal.inria.fr/hal-01002693
Contributor : Fabrice Jouanot <>
Submitted on : Friday, June 6, 2014 - 3:43:46 PM
Last modification on : Wednesday, February 27, 2019 - 1:25:03 AM

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  • HAL Id : hal-01002693, version 1

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Remi Tournaire, Alexandre Termier, Jean-Marc Petit, Marie-Christine Rousset. Discovery of Probabilistic Mappings between Taxonomies: Principles and Experiments. Journées Bases de Données Avancées (BDA 2009), 2009, namur, Belgium, Belgium. pp.1--12. ⟨hal-01002693⟩

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