Deriving similarity for Semantic Web using similarity graph

Juhum Kwon, O. Hoon Choi, Chang Joo Moon, Soo Hyun Park, Doo Kwon Baik

Research output: Contribution to journalArticle

11 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)149-166
Number of pages18
JournalJournal of Intelligent Information Systems
Volume26
Issue number2
DOIs
Publication statusPublished - 2006 Mar 1
Externally publishedYes

Fingerprint

Semantic Web
Ontology
Interoperability
Semantics

Keywords

  • Mapping rules
  • Ontology
  • Semantic web
  • Similarity graph
  • WordNet

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

Deriving similarity for Semantic Web using similarity graph. / Kwon, Juhum; Choi, O. Hoon; Moon, Chang Joo; Park, Soo Hyun; Baik, Doo Kwon.

In: Journal of Intelligent Information Systems, Vol. 26, No. 2, 01.03.2006, p. 149-166.

Research output: Contribution to journalArticle

Kwon, Juhum ; Choi, O. Hoon ; Moon, Chang Joo ; Park, Soo Hyun ; Baik, Doo Kwon. / Deriving similarity for Semantic Web using similarity graph. In: Journal of Intelligent Information Systems. 2006 ; Vol. 26, No. 2. pp. 149-166.
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