An Interactive, Asymmetric and Extensional Method for Matching Conceptual Hierarchies

Our work deals with schema or ontology matching and is driven by the following statements: (1) Most of works only consider intensional description of schemas; (2) They mostly use symmetric similarity measures (and then they match similarity relations betwen concepts); (3) Few prototypes allow an interactive and visual match process. Therefore, we suggest an extensional and asymmetric matching method based on the discovery of significant implication rules between concepts described in textual documents. Our approach relies on the association rules paradigm and use a probabilistic model of deviation from independence, named implication intensity. Our matching method is divided into two consecutive stages: (1) the extraction in documents of relevant terms for each concept; (2) the discovery of significant implications between the concepts. And finally, we enclose this matching approach into an interactive visualization tool in order to facilitate the analyse, the validation and the editing of a mapping set for the knowledge engineer.