• DocumentCode
    2054961
  • Title

    Construction of High-quality Feature Extension Mode Library for Chinese Short-text Classification

  • Author

    Fan, Xinghua ; Hu, Hongge

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Chongqing Univ. of Posts & Telecommun., Chongqing, China
  • Volume
    2
  • fYear
    2010
  • fDate
    14-15 Aug. 2010
  • Firstpage
    87
  • Lastpage
    90
  • Abstract
    One feasible way to handle the difficulties in the Chinese short-text classification is doing feature extension for its content. And a key technique of it is the construction of feature extension mode library whose quality would directly influence the effect of feature extension. This paper proposes a method of constructing a high-quality feature extension mode library. In our method, firstly, we obtained the feature extension modes from the training set, and then introduced three measures, i.e., confidence, category homoplasy and relevancy strength of the obtained feature extension mode, to improve their quality. Finally, we used the high-quality feature extension modes to construct a high-quality feature extension mode library. Experimental results show that (1) Introducing the three measures can improve the quality of feature extension mode in some degree respectively; (2)A high-quality feature extension mode library is helpful to improving the effect of Chinese short-text classification.
  • Keywords
    pattern classification; text analysis; Chinese short-text classification; category homoplasy measurement; confidence measurement; feature extension mode library; relevancy strength measurement; Association rules; Finance; Lead; Libraries; Noise; Text categorization; Training; Chinese short-text classification; category homoplasy; confidence; high-quality feature extension mode library; relevancy strength;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering (ICIE), 2010 WASE International Conference on
  • Conference_Location
    Beidaihe, Hebei
  • Print_ISBN
    978-1-4244-7506-3
  • Electronic_ISBN
    978-1-4244-7507-0
  • Type

    conf

  • DOI
    10.1109/ICIE.2010.117
  • Filename
    5571259