• DocumentCode
    2029670
  • Title

    The study in ranking method for web entity

  • Author

    Li, Peng

  • Author_Institution
    Inf. Technol. Coll., Eastern Liaoning Univ., Dandong, China
  • Volume
    4
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    1587
  • Lastpage
    1591
  • Abstract
    Along with the rapidly development of the information retrieval and web technology, web entity retrieval has become a new popular way for getting specific information, such as looking for a book or a movie. Like document retrieval, generally there are too many results returned for a query, so ranking is still a necessary step during the entity retrieval process. This paper will focus on the ranking problem for web entity. Two methods are proposed, the first one will rank the results by a relevance score directly and the second one get the final ranking list by a training model. To compare the effective of the two methods, by the same features, we perform related experiments. According to the test data from real web pages, we test the precise of each method and get the conclusion at last.
  • Keywords
    Internet; information retrieval; document retrieval; information retrieval; ranking method; relevance score; training model; web entity retrieval; web pages; web technology; Chemistry; Information retrieval; Research and development; Support vector machines; Training; Training data; entity retrieval; feature; ranking; relevance score;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5931-5
  • Type

    conf

  • DOI
    10.1109/FSKD.2010.5569354
  • Filename
    5569354