• DocumentCode
    3105218
  • Title

    Ontology Population from Unstructured and Semi-structured Texts

  • Author

    Yoon, Hee-Geun ; Han, Yong Jin ; Park, Seong-Bae ; Park, Se-Young

  • fYear
    2007
  • fDate
    22-24 Aug. 2007
  • Firstpage
    135
  • Lastpage
    139
  • Abstract
    Legacy information search systems have limitation that it does not consider semantic information but just lexical information such as keywords. A semantic web is expected to solve such limitation of present systems. In constructing semantic web, an ontology is believed to be a must. However, the ontology construction is very difficult. It requires great human efforts, since the creation of individuals is a time consuming task. Thus, there is a potential need for automatic or semiautomatic ontology population system, which greatly alleviates the human efforts. This paper proposes a method for an ontology population, in which the population is processed by computing the overlap between instances and concepts. This method is very simple but shows high performance.
  • Keywords
    Costs; Data mining; Humans; Information technology; Learning systems; Logic; Machine learning; Ontologies; Semantic Web; World Wide Web; ontology population;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Language Processing and Web Information Technology, 2007. ALPIT 2007. Sixth International Conference on
  • Conference_Location
    Luoyang, Henan, China
  • Print_ISBN
    978-0-7695-2930-1
  • Type

    conf

  • DOI
    10.1109/ALPIT.2007.30
  • Filename
    4460628