Sabou, Marta; d'Aquin, Mathieu and Motta, Enrico
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While current approaches to ontology mapping produce good results by mainly relying on label and structure based similarity measures, there are several cases in which they fail to discover important mappings. In this paper we describe a novel approach to ontology mapping, which is able to avoid this limitation by using background knowledge. Existing approaches relying on background knowledge typically have one or both of two key limitations: 1) they rely on a manually selected reference ontology; 2) they suffer from the noise introduced by the use of semi-structured sources, such as text corpora. Our technique circumvents these limitations by exploiting the increasing amount of semantic resources available online. As a result, there is no need either for a manually selected reference ontology (the relevant ontologies are dynamically selected from an online ontology repository), or for transforming background knowledge in an ontological form. The promising results from experiments on two real life thesauri indicate both that our approach has a high precision and also that it can find mappings, which are typically missed by existing approaches.
|Item Type:||Conference Item|
|Copyright Holders:||2006 The Authors|
|Extra Information:||OM-2006 Ontology Matching
Proceedings of the 1st International Workshop on Ontology Matching (OM-2006)
Collocated with the 5th International Semantic Web Conference (ISWC-2006)
Athens, Georgia, USA, November 5, 2006.
Edited by Pavel Shvaiko, Jérôme Euzenat, Natalya Noy, Heiner Stuckenschmidt, Richard Benjamins, Michael Uschold
|Keywords:||ontology mapping; background knowledge; semantic web|
|Academic Unit/Department:||Knowledge Media Institute|
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Kay Dave|
|Date Deposited:||01 Apr 2011 09:51|
|Last Modified:||24 Feb 2016 20:21|
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