• DocumentCode
    145234
  • Title

    Aggregation of Ontology Matchers in Lieu of a Reference Ontology

  • Author

    Al Boni, Mohammad ; Anderson, Derek T.

  • Author_Institution
    Center for Adv. Vehicular Syst., Mississippi State Univ., Starkville, MS, USA
  • Volume
    1
  • fYear
    2014
  • fDate
    10-13 March 2014
  • Firstpage
    353
  • Lastpage
    359
  • Abstract
    Ontologies are widely used to represent knowledge in different domains. As a result, numerous methods have been put forth to match ontologies. No technique has been shown to be robust across all domains. Furthermore, ontology matchers typically make use of a reference ontology. However, this is not guaranteed to exist. In this article, the fuzzy integral is used to aggregate multiple ontology matchers in lieu of a reference ontology. Specifically, we present a way to derive the fuzzy measure based on ideas from crowd sourcing when the worth of individuals is not known. Preliminary results are presented to show the robustness of our approach across different domains.
  • Keywords
    fuzzy set theory; knowledge representation languages; ontologies (artificial intelligence); crowd sourcing; fuzzy integral; knowledge representation language; ontology matcher aggregation; reference ontology; Frequency modulation; Measurement; Ontologies; Robustness; Sociology; Standards; Statistics; crowd sourcing; fuzzy integral; fuzzy measure; measure of agreement; ontology matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Computational Intelligence (CSCI), 2014 International Conference on
  • Conference_Location
    Las Vegas, NV
  • Type

    conf

  • DOI
    10.1109/CSCI.2014.67
  • Filename
    6822134