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Opening the Black Box of Ontology Matching

Duy Hoa Ngo 1 Zohra Bellahsene 2 Konstantin Todorov 1
1 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
2 FADO - Fuzziness, Alignments, Data & Ontologies
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Due to the high heterogeneity of ontologies, a combination of many methods is necessary in order to discover correctly the semantic correspondences between their elements. An ontology matching tool can be seen as a collection of several matching components, each implementing a specific method dealing with a specific heterogeneity type (terminological, structural or semantic). In addition, a mapping selection module is introduced to filter out the most likely mapping candidates. This paper proposes an empirical study of the interaction between these components working together inside an ontology matching system. By the help of datasets from the Ontology Alignment Evaluation Initiative, we have carried out several experimental studies. In the first place, we have been interested in the impact of the mapping selection module on the performance of terminological and structural matchers revealing the advantage of using global methods vs. local ones. Further, we have carried an extensive study on the flaw of the performance of a structural matcher in the presence of noisy input coming from a terminological method. Finally, we have analyzed the behavior of a structural and a semantic component with respect to inputs taken from different terminological matchers.
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Submitted on : Wednesday, January 30, 2019 - 11:41:29 AM
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Duy Hoa Ngo, Zohra Bellahsene, Konstantin Todorov. Opening the Black Box of Ontology Matching. ESWC: European Semantic Web Conference, May 2013, Montpellier, France. pp.16-30, ⟨10.1007/978-3-642-38288-8_2⟩. ⟨lirmm-00864960⟩



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