Combining Logic and Probabilities for Discovering Mappings between Taxonomies (short paper)

Remi Tournaire; Jean-Marc Petit; Marie-Christine Rousset; Alexandre Termier

Combining Logic and Probabilities for Discovering Mappings between Taxonomies (short paper)

Remi Tournaire ¹ Jean-Marc Petit ² Marie-Christine Rousset ¹ Alexandre Termier ¹

1 LIG Laboratoire d'Informatique de Grenoble - HADAS

LIG - Laboratoire d'Informatique de Grenoble

2 BD - Base de Données

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.

Document type :

Conference papers

Domain :

Computer Science [cs] / Artificial Intelligence [cs.AI]

Complete list of metadatas

https://hal.inria.fr/hal-00953266
Contributor : Fabrice Jouanot <>
Submitted on : Friday, February 28, 2014 - 11:12:17 AM
Last modification on : Saturday, March 30, 2019 - 1:08:54 AM

Combining Logic and Probabilities for Discovering Mappings between Taxonomies (short paper)

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Combining Logic and Probabilities for Discovering Mappings between Taxonomies (short paper)

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