• DocumentCode
    2539451
  • Title

    Personalized search based on learning user click history

  • Author

    Chen, Cheqian ; Lin, Kequan ; Li, Heshan ; Dong, Shoubin

  • Author_Institution
    Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
  • fYear
    2010
  • fDate
    7-9 July 2010
  • Firstpage
    490
  • Lastpage
    495
  • Abstract
    Nowadays, Web Search Engines have become an indispensable tool for people to find internet resources. However, current Web Search Engines still have many drawbacks. They serve all people in the same way, regardless of the individual needs of each user, which obviously cannot satisfy most of the users. Personalized Search is proposed to solve this problem and to improve the retrieve quality. This paper deeply investigates the approach for personalized search, and has proposed a practical and effective method.
  • Keywords
    Internet; personal information systems; query processing; search engines; Internet resources; Web search engines; learning user click history; personalized search; query expansion; Algorithm design and analysis; Bayesian methods; Classification algorithms; Search engines; Sorting; Support vector machines; Training; Personalization; clickthrough data; search engine; user preferences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-8041-8
  • Type

    conf

  • DOI
    10.1109/COGINF.2010.5599689
  • Filename
    5599689