Discovery of Probabilistic Mappings between Taxonomies: Principles and Experiments

Rémi Tournaire (1, 2) , Jean-Marc Petit (1) , Marie-Christine Rousset (2) , Alexandre Termier (2)

1 BD - Base de Données
2 HADAS - Heterogeneous and Adaptive distributed DAta management Systems

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.

Domaines: Base de données [cs.DB]

Rémi Tournaire, Jean-Marc Petit, Marie-Christine Rousset, Alexandre Termier. Discovery of Probabilistic Mappings between Taxonomies: Principles and Experiments. Journal on Data Semantics, 2011, 6720, pp.66-101. ⟨10.1007/978-3-642-22630-4_3⟩. ⟨hal-00932491⟩