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Combining Logic and Probabilities for Discovering Mappings Between Taxonomies

Rémi Tournaire 1 Jean-Marc Petit 2 Marie-Christine Rousset 1 Alexandre Termier 1
1 HADAS - Heterogeneous and Adaptive distributed DAta management Systems
LIG - Laboratoire d'Informatique de Grenoble
2 LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
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 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-00953265
Contributor : Fabrice Jouanot <>
Submitted on : Friday, February 28, 2014 - 11:12:16 AM
Last modification on : Thursday, January 14, 2021 - 3:44:05 PM

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  • HAL Id : hal-00953265, version 1

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LIG_TDCGE_HADAS | LIG_TDCGE | LIG | CNRS | EC-LYON | LIRIS | INSA-LYON | UNIV-LYON1 | INSA-GROUPE | LABEXIMU | UNIV-LYON2 | UDL | UGA

Citation

Rémi Tournaire, Jean-Marc Petit, Marie-Christine Rousset, Alexandre Termier. Combining Logic and Probabilities for Discovering Mappings Between Taxonomies. Proceedings of the 4th International Conference on Knowledge Science, Engineering and Management, 2010, Belfast, Ireland. pp.530--542. ⟨hal-00953265⟩

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