• DocumentCode
    255967
  • Title

    Heavy weight ontology learning using text documents

  • Author

    Kumar, V. ; Chaudhary, S.

  • Author_Institution
    ABES Eng. Coll., Ghaziabad, India
  • fYear
    2014
  • fDate
    11-13 Dec. 2014
  • Firstpage
    110
  • Lastpage
    114
  • Abstract
    Ontology plays an important role not only for data processing in knowledge based systems but also, provide interoperability in heterogeneous environment and is a cornerstone of semantic web technology. The required technology is used for knowledge representation in OWL/RDF format and facilitate faster access of concepts in domain of interest. Development of ontology is a tedious job and requires a lot of man power in terms of experts´ time and knowledge. Although there are various tools and techniques for light weight ontology learning; yet full automation of heavy weight ontology learning from text documents is a distant dream. In this paper we have proposed a framework for learning heavy weight ontology, using text documents written in English language. Initial experimental results are shown for demonstration of our on going research.
  • Keywords
    learning (artificial intelligence); ontologies (artificial intelligence); text analysis; English language; heavy weight ontology learning; text documents; Agriculture; Educational institutions; Grid computing; Knowledge based systems; Mobile handsets; Ontologies; Semantics; Android application; Knowledge base; Ontology learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel, Distributed and Grid Computing (PDGC), 2014 International Conference on
  • Conference_Location
    Solan
  • Print_ISBN
    978-1-4799-7682-9
  • Type

    conf

  • DOI
    10.1109/PDGC.2014.7030725
  • Filename
    7030725