Abstract
Nowadays, many ontologies are used in industry, public adminstration and academia. Although these ontologies are developed for various purposes and domains, they often contain overlapping information. To build a collaborative semantic web, which allows data to be shared and reused across applications, enterprises, and community boundaries, it is necessary to find ways to compare, match and integrate various ontologies. Different strategies (e.g., string similarity, synonyms, structure similarity and based on instances) for determining similarity between entities are used in current ontology matching systems. Synonyms can help to solve the problem of using different terms in the ontologies for the same concept. The WordNet thesauri can support improving similarity measures. This paper provides an overview of how to apply WordNet in the ontology matching research area.
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Lin, F., Sandkuhl, K. (2008). A Survey of Exploiting WordNet in Ontology Matching. In: Bramer, M. (eds) Artificial Intelligence in Theory and Practice II. IFIP AI 2008. IFIP – The International Federation for Information Processing, vol 276. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09695-7_33
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DOI: https://doi.org/10.1007/978-0-387-09695-7_33
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