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Deriving similarity for Semantic Web using similarity graph

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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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Authors and Affiliations

  1. 225-Ho, Asan Science Building, 1, 5-ka, Anam-dong, Sungbuk-ku, Seoul, 136-701, South Korea

    JuHum Kwon, O-Hoon Choi & Doo-Kwon Baik

  2. Department of Computer Science, Konkuk University, 322 Danwol-dong, Chungju-si, Chungcheongbuk-do, 380-701, Seoul, South Korea

    Chang-Joo Moon

  3. Kookmin University, 861-1, Chongnung-Dong, Songbuk-Gu, Seoul, 136-702, South Korea

    Soo-Hyun Park

Authors
  1. JuHum Kwon
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  2. O-Hoon Choi
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  3. Chang-Joo Moon
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  4. Soo-Hyun Park
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  5. Doo-Kwon Baik
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Corresponding author

Correspondence to Chang-Joo Moon.

Additional information

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

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