• DocumentCode
    3593082
  • Title

    Personalized Information Recommendation Model Based on Semantic Grid

  • Author

    Sun, Yusheng ; Dong, Hui

  • Author_Institution
    Center for Studies of Inf. Resources, Wuhan Univ., Wuhan, China
  • Volume
    1
  • fYear
    2009
  • Firstpage
    52
  • Lastpage
    57
  • Abstract
    In this paper, we analyzed the drawbacks existing in the current personalized information recommendation. Then we analyzed the limitations of the application of the Internet, the semantic Web and the grid technology in the field of personalized information recommendation. Ground on the analysis above, we put forward a personalized information recommendation model based on semantic grid, and preliminary advanced the personalized information recommendation solution of large-scale, high accuracy, strong timeliness, which is geared to the distributed, heterogeneous, massive information environment. Specifically speaking, the solution makes use of the high-performance computing and information service capability of semantic grid to resolve the problem of recommendation scale and timeliness; it makes use of the semantic processing ability of semantic grid to resolve the problem of recommendation intelligence; In addition, it makes use of the grid monitoring technology to resolve the problem of the real time information acquisition of the candidate grid nodes.
  • Keywords
    Internet; grid computing; information filters; Internet application limitation; high performance computing; information service capability; massive information environment; personalized information recommendation model; real time information acquisition; semantic grid; Distributed computing; Energy management; Environmental management; Grid computing; Information analysis; Information resources; Internet; Resource management; Semantic Web; Sun; PIR; personalized information; semantic grid;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
  • Print_ISBN
    978-0-7695-3605-7
  • Type

    conf

  • DOI
    10.1109/CSO.2009.246
  • Filename
    5193641