• DocumentCode
    2967617
  • Title

    GAOM: Genetic Algorithm Based Ontology Matching

  • Author

    Wang, Junli ; Ding, Zhijun ; Jiang, ChangJun

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Tongji Univ., Shanghai
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    617
  • Lastpage
    620
  • Abstract
    In this paper a genetic algorithm-based optimization procedure for ontology matching problem is presented as a feature-matching process. First, from a global view, we model the problem of ontology matching as an optimization problem of a mapping between two compared ontologies, and every ontology has its associated feature sets. Second, as a powerful heuristic search strategy, genetic algorithm is employed for the ontology matching problem. Given a certain mapping as optimizing object for GA, fitness function is defined as a global similarity measure function between two ontologies based on feature sets. Finally, a set of experiments are conducted to analysis and evaluate the performance of GA in solving ontology matching problem
  • Keywords
    feature extraction; genetic algorithms; ontologies (artificial intelligence); feature matching; fitness function; genetic algorithm; global similarity measure function; ontology matching; optimization; Computer science; Educational institutions; Genetic algorithms; Genetic engineering; Information science; Ontologies; Performance analysis; Semantic Web; Taxonomy; Virtual colonoscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Services Computing, 2006. APSCC '06. IEEE Asia-Pacific Conference on
  • Conference_Location
    Guangzhou, Guangdong
  • Print_ISBN
    0-7695-2751-5
  • Type

    conf

  • DOI
    10.1109/APSCC.2006.59
  • Filename
    4041300