• DocumentCode
    1694146
  • Title

    Condorcet Fusion for Blog Opinion Retrieval

  • Author

    Wu, Shengli ; Zeng, Xiaoqin

  • Author_Institution
    Sch. of Comput. & Telecommun., Jiangsu Univ., Zhenjiang, China
  • fYear
    2012
  • Firstpage
    156
  • Lastpage
    160
  • Abstract
    Blogs have been popular social networking platforms in recent years. Blog opinion retrieval is one of the key issues that needs to be solved. In this paper, we investigate if the Condorcet fusion and the weighted Condorcet fusion can be used for effectiveness improvement of blog opinion retrieval. The experiments carried out with the data set from the TREC 2008 Blog track show that the Condorcet fusion is effective and the weighted Condorcet fusion, with its weights trained by linear discriminant analysis, is very effective. Both of them outperform the best component result by a clear margin.
  • Keywords
    information retrieval; search engines; sensor fusion; social networking (online); statistical analysis; TREC 2008 Blog track; blog opinion retrieval; data set; linear discriminant analysis; search engines; social networking platforms; weighted Condorcet fusion; Analytical models; Blogs; Educational institutions; Training; USA Councils; condorcet fusion; data fusion; information retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database and Expert Systems Applications (DEXA), 2012 23rd International Workshop on
  • Conference_Location
    Vienna
  • ISSN
    1529-4188
  • Print_ISBN
    978-1-4673-2621-6
  • Type

    conf

  • DOI
    10.1109/DEXA.2012.23
  • Filename
    6327419