• DocumentCode
    2608214
  • Title

    Web document retrieval using manifold learning and ACO algorithm

  • Author

    Ziqiang, Wang ; Xia, Sun

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
  • fYear
    2009
  • fDate
    18-20 Oct. 2009
  • Firstpage
    152
  • Lastpage
    155
  • Abstract
    To efficiently deal with high dimensionality and precision problems in document retrieval, a novel document retrieval algorithm based on manifold learning and ant colony optimization(ACO) algorithm is proposed. The high-dimensional document data are first projected into lower-dimensional feature space with neighborhood preserving embedding (NPE) algorithm, the ACO algorithm is then applied to retrieve relevant documents in the reduced lower-dimensionality document feature space. Extensive experiments on real-world data set demonstrate the effectiveness of the proposed algorithm.
  • Keywords
    Internet; document handling; information retrieval; learning (artificial intelligence); optimisation; ACO algorithm; NPE algorithm; Web document retrieval algorithm; ant colony optimization; high-dimensional document data; lower-dimensional feature space; manifold learning; neighborhood preserving embedding; Ant colony optimization; Feedback; Information retrieval; Large scale integration; Linear discriminant analysis; Manifolds; Pattern recognition; Scattering; Space technology; Sun; Document retrieval; ant colony optimization(ACO); manifold learning; neighborhood preserving embedding(NPE);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Broadband Network & Multimedia Technology, 2009. IC-BNMT '09. 2nd IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4590-5
  • Electronic_ISBN
    978-1-4244-4591-2
  • Type

    conf

  • DOI
    10.1109/ICBNMT.2009.5348468
  • Filename
    5348468