Abstract
One important research challenge of current Semantic Web is resolving the interoperability issue across ontologies. The issue is directly related to identifying semantics of resources residing in different domain ontologies. That is, the semantics of a concept in an ontology differs from others according to the modeling style and intuition of the knowledge expert even though they are the same forms of a concept in each respective ontology. In this paper, we propose a similarity measure to resolve the interoperability issue by using a similarity graph. The strong point of this paper is that we provide a precise mapping technique and similarity properties to derive the similarity. The novel contribution of this paper is that we provide a core technique of computing similarity across ontologies of Semantic Web.
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This research was supported by the MIC (Ministry of Information and Communication), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute of Information Technology Assessment).
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Kwon, J., Choi, OH., Moon, CJ. et al. Deriving similarity for Semantic Web using similarity graph. J Intell Inf Syst 26, 149–166 (2006). https://doi.org/10.1007/s10844-006-0199-1
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DOI: https://doi.org/10.1007/s10844-006-0199-1