• DocumentCode
    1948567
  • Title

    A Semantic Vector Retrieval Model for Desktop Documents

  • Author

    Sheng, Li

  • Author_Institution
    Sch. of Inf., Zhongnan Univ. of Economic & Law, Wuhan
  • Volume
    1
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    682
  • Lastpage
    685
  • Abstract
    The paper provides a semantic vector retrieval model for desktop documents based on the ontology. Comparing with traditional vector space model, the semantic model using semantic and ontology technology to solve several problems that traditional model could not overcome such as the shortcomings of weight computing based on statistical method, the expression of semantic relations between different keywords, the description of document semantic vectors and the similarity calculating, etc. Finally, the experimental results show that the retrieval ability of our new model has significant improvement both on recall and precision.
  • Keywords
    document handling; information retrieval; ontologies (artificial intelligence); desktop documents; document semantic vectors; ontologyontology technology; semantic vector retrieval model; similarity calculating; statistical method; weight computing; Computer science; Frequency; Information retrieval; Inverse problems; Ontologies; Semantic Web; Software engineering; Space technology; Statistical analysis; Technology management; information retrieval; ontology; samntic desktop; vector retrieval model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.421
  • Filename
    4721841