• DocumentCode
    3113651
  • Title

    Ontology-based semantic similarity: A new approach based on analysis of the concept intent

  • Author

    Jian-Bo Gao ; Bao-Wen Zhang ; Xiao-Hua Chen

  • Author_Institution
    Inf. Security Dept., Shanghai Jiao Tong Univ., Shanghai, China
  • Volume
    02
  • fYear
    2013
  • fDate
    14-17 July 2013
  • Firstpage
    676
  • Lastpage
    681
  • Abstract
    Ontology offers a structured knowledge representation and provides formal interpretation of concepts which can be used in semantic similarity measuring. In this paper, we analyze these ontology-based approaches for semantic similarity computation and propose a new ontology-based measure relying on exploiting intent of the concept. Our measurement combines the idea of two popular semantic similarity calculation approaches: graph-based approaches and feature-based measures. In order to compute the semantic similarity of concepts in ontology, a new algorithm is presented. We compare results obtained by our method with other two typical approaches, the results show that our measurement can distinguish fine differences between concepts and thus has finer granularity.
  • Keywords
    graph theory; ontologies (artificial intelligence); concept intent; feature-based measures; graph-based approach; ontology-based measure; ontology-based semantic similarity; structured knowledge representation; Abstracts; Equations; Mathematical model; Semantics; Concept intent; Feature-based measure; Formal; Ontology; Semantic similarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
  • Conference_Location
    Tianjin
  • Type

    conf

  • DOI
    10.1109/ICMLC.2013.6890375
  • Filename
    6890375