• DocumentCode
    2121034
  • Title

    New Algorithm for Building Ontology from Existing Rules: A Case Study

  • Author

    Kharbat, Faten ; Ghalayini, Haya

  • Author_Institution
    Dept. of Comput. Sci., Zarqa Private Univ., Zarqa
  • fYear
    2009
  • fDate
    3-5 April 2009
  • Firstpage
    12
  • Lastpage
    16
  • Abstract
    From the fact that ontologies can help in making sense of huge amount of content, this paper proposes a case study for building ontology via set of rules generated by rule-based learning system. The proposed algorithm utilises the extracted and representative rules generated from the original dataset in developing ontology elements. The proposed algorithm is applied to a well known dataset in the breast cancer domain. The results are encouraging and support the potential role that this approach can play in providing a suitable starting point for ontology development.
  • Keywords
    cancer; data mining; learning (artificial intelligence); medical computing; ontologies (artificial intelligence); Wisconsin breast cancer dataset; data mining; domain ontology; rule generation; rule-based learning system; Artificial intelligence; Breast cancer; Computer science; Information management; Knowledge representation; Learning systems; Logic; Ontologies; Semantic Web; Spine; Onrology; breast cancer; developing Ontology; knowldege-based systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Management and Engineering, 2009. ICIME '09. International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-0-7695-3595-1
  • Type

    conf

  • DOI
    10.1109/ICIME.2009.16
  • Filename
    5076989