• DocumentCode
    588703
  • Title

    Region-Based Ranking in Association Analysis for News Relation Discovery

  • Author

    Kittiphattanabawon, N. ; Theeramunkong, Thanaruk ; Nantajeewarawat, Ekawit

  • Author_Institution
    Sirindhorn Int. Inst. of Technol., Thammasat Univ., Bangkok, Thailand
  • fYear
    2012
  • fDate
    8-10 Nov. 2012
  • Firstpage
    187
  • Lastpage
    194
  • Abstract
    Using an association-based technique to find associations among news documents can obtain useful news relations. However, existing works may not detect meaningful relations since only single association measure was used to mine news relations. This paper presents a region-based ranking approach to selectively use different association measures for different ranking regions, towards improvement of the ranking mechanism for news relation discovery. To evaluate region-based ranking, the method is compared to the conventional ranking method, which has no region construction. As performance evaluation, the top-k results of each method are compared using rank-order mismatch (ROM). Compared to the non-region method, the region-based method can find meaningful relations among news with the average ROM improvement of 1.21% - 28.32% for confidence and 4.83% - 29.04% for conviction, respectively.
  • Keywords
    data mining; document handling; ROM; association analysis; news documents; news relation discovery; rank-order mismatch; region-based ranking; Association rules; Educational institutions; Frequency measurement; Linear programming; Read only memory; Weight measurement; association rule mining; news relation discovery; rank-order mismatch; region-based ranking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge, Information and Creativity Support Systems (KICSS), 2012 Seventh International Conference on
  • Conference_Location
    Melbourne, VIC
  • Print_ISBN
    978-1-4673-4564-4
  • Type

    conf

  • DOI
    10.1109/KICSS.2012.34
  • Filename
    6405528