• DocumentCode
    3092034
  • Title

    Study on question-answering system of restricted domain based on knowledge base

  • Author

    Liu, Wen-hua ; Kang, Hai-Yan

  • Author_Institution
    Comput. Sch., Beijing Inf. Sci. & Technol. Univ., Beijing, China
  • Volume
    4
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    2260
  • Lastpage
    2264
  • Abstract
    Large scale texts as the knowledge base of extracting answer can ensure the accuracy of information resources and also make information convenient for management. This paper presents the development of question answer system of restricted domain based on knowledge base and proposes an answer extraction method based on the sentence similarity and organization names, and which implements the study of question answering system of restricted domain based on knowledge base. The experiments prove that the introduction of organization names not only greatly improves the segmentation accuracy in the module of words segmentation but also improves the retrieval efficiency of system and the accuracy of answer extraction.
  • Keywords
    belief networks; knowledge based systems; natural language processing; text analysis; answer extraction method; organization names; question answering system; sentence similarity; texts knowledge base; words segmentation module; Conference management; Cybernetics; Information management; Information science; Knowledge management; Large-scale systems; Libraries; Machine learning; Resource management; Technology management; Organization-names; Question-answering system of restricted domain; Sentence similarity; Texts knowledge base;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212239
  • Filename
    5212239