• DocumentCode
    3497412
  • Title

    A Domain Adaptive Ontology Learning Framework

  • Author

    Nie, Xuejun ; Zhou, Jingli

  • Author_Institution
    Huazhong Univ. of Sci. & Technol., Wuhan
  • fYear
    2008
  • fDate
    6-8 April 2008
  • Firstpage
    1726
  • Lastpage
    1729
  • Abstract
    Ontology leaning is a solution to the bottleneck of knowledge acquisition and time-consuming construction of ontologies. In recent years, a lot of research work has been done to design appropriate methods for ontology learning. However, all these methods suffer from some common shortcomings which prevent wide production and usage of ontologies. In this paper, we first analyze the characteristics of these shortcomings and then proposed an ontology learning framework OntoExtractor, which includes seed concept extraction, semantic relationships construction and ontology refinement. As the result shows, this framework could provide good domain adaptability for ontology learning system.
  • Keywords
    knowledge acquisition; learning systems; ontologies (artificial intelligence); OntoExtractor; domain adaptability; domain adaptive ontology learning; knowledge acquisition; ontology learning system; ontology refinement; seed concept extraction; semantic relationships construction; Buildings; Data mining; Design methodology; Information analysis; Instruments; Knowledge acquisition; Learning systems; Ontologies; Production; Semantic Web;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control, 2008. ICNSC 2008. IEEE International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4244-1685-1
  • Electronic_ISBN
    978-1-4244-1686-8
  • Type

    conf

  • DOI
    10.1109/ICNSC.2008.4525501
  • Filename
    4525501