• DocumentCode
    2143126
  • Title

    Ontology Building from Incomplete Information System Based on Granular Computing

  • Author

    Li, Xiangjun ; Qiu, Taorong ; Liu, Qing ; Bai, Xiaoming

  • Author_Institution
    Dept. of Comput., Nanchang Univ., Nanchang, China
  • fYear
    2010
  • fDate
    14-16 Aug. 2010
  • Firstpage
    292
  • Lastpage
    296
  • Abstract
    With the development of web, there are an increasing number of incomplete information systems. Approaches to building ontology from this kind of data source have become much more important. Granular computing (GrC) is a nature way of human problem-solving. It is intended to deal with impression, uncertainty, and partial truth. In this paper, by applying the principle of granular computing and concept lattice, a granular model of ontology building from multi-valued incomplete information systems was described. A domain concept granule and a domain concept granule lattice were presented. An algorithm of generating the domain concept granule lattice was proposed. With the domain concept granule lattice, ontology building can be fulfilled. A real world example illustrated shows that the proposed algorithm is effective and feasible. Therefore, granular computing should be of great help in representing and constructing ontologies.
  • Keywords
    information systems; ontologies (artificial intelligence); problem solving; rough set theory; semantic Web; uncertainty handling; data source; domain concept granule lattice; granular computing; human problem-solving; multivalued incomplete information systems; ontology building; web development; Approximation methods; Buildings; Computational modeling; Context; Information systems; Lattices; Ontologies; granular computing; information granule; ontology; ontology building;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2010 IEEE International Conference on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    978-1-4244-7964-1
  • Type

    conf

  • DOI
    10.1109/GrC.2010.100
  • Filename
    5575962