A Generic Approach for Combining Linguistic and Context Profile Metrics in Ontology Matching

Duy Hoa Ngo 1, 2 Zohra Bellahsene 2 Remi Coletta 2
2 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Ontology matching is needed in many application domains. In this paper, we present a machine learning approach for combining metrics, which exploits various linguistic and context profiles features in order to discover mappings between entities of different ontologies. Our approach has been implemented and the experimental results over Benchmark and Conference test cases on OAEI 2010 campaign demonstrate its effectiveness and efficiency in terms of quality of matching and flexibility.
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Communication dans un congrès
Robert Meersman and al. ODBASE'2011: 10th International Conference on Ontologies, DataBases, and Applications of Semantics, Oct 2011, Crete, Greece. pp.800-807, 2011, LNCS. 〈http://www.onthemove-conferences.org/index.php/odbase11〉
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Soumis le : mercredi 9 novembre 2011 - 18:01:20
Dernière modification le : jeudi 24 mai 2018 - 15:59:21
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Duy Hoa Ngo, Zohra Bellahsene, Remi Coletta. A Generic Approach for Combining Linguistic and Context Profile Metrics in Ontology Matching. Robert Meersman and al. ODBASE'2011: 10th International Conference on Ontologies, DataBases, and Applications of Semantics, Oct 2011, Crete, Greece. pp.800-807, 2011, LNCS. 〈http://www.onthemove-conferences.org/index.php/odbase11〉. 〈lirmm-00639714〉

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