• DocumentCode
    3258863
  • Title

    Domain Ontology Learning from Websites

  • Author

    Zhao, Yu ; Li, Jianqiang

  • Author_Institution
    NEC Labs. China, Beijing, China
  • fYear
    2009
  • fDate
    20-24 July 2009
  • Firstpage
    129
  • Lastpage
    132
  • Abstract
    This paper proposes a novel method to learn light-weight domain ontology from the Web. To create ontology (semi-) automatically has been a challenging and critical problem to make Semantic Web come true. Many methods have been reported on ontology learning from the Web by analyzing the page contents. However, they are not applicable for learning ontology from organization Websites, where the description of a concept or an individual is distributed across multiple Web pages, and the ontological information can only be discovered by considering Website structure. We propose a Website structure based method to extract organizational ontology from organization Websites. Multiple organizational ontology of the same domain can be merged into domain ontology. This method employs both the intra-page and inter-page hierarchical relations hidden in Website structure for ontology learning. The empirical experiments show the effectiveness of this approach.
  • Keywords
    Web sites; computer aided instruction; ontologies (artificial intelligence); semantic Web; Website; domain ontology learning; organizational ontology; semantic Web; Data mining; Internet; Laboratories; Microcomputers; National electric code; Navigation; Ontologies; Personal communication networks; Semantic Web; Web pages; domain ontology; hierarchy; ontology learning; web mining; website structure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications and the Internet, 2009. SAINT '09. Ninth Annual International Symposium on
  • Conference_Location
    Bellevue, WA
  • Print_ISBN
    978-1-4244-4776-3
  • Electronic_ISBN
    978-0-7695-3700-9
  • Type

    conf

  • DOI
    10.1109/SAINT.2009.29
  • Filename
    5230647