• DocumentCode
    3275174
  • Title

    Research on enhancing the effectiveness of the Chinese text automatic categorization based on ICTCLAS segmentation method

  • Author

    Xiangdong Li ; Cheng Zhang

  • Author_Institution
    Center for Studies of Inf. Resources, Wuhan Univ., Wuhan, China
  • fYear
    2013
  • fDate
    23-25 May 2013
  • Firstpage
    267
  • Lastpage
    270
  • Abstract
    The article proposed a method that suggest a way to replace some lower category identification capacity items from the ICTCLAS segmentation result by drawing the feature items that owns a better category identification capacity from the 2-gram segmentation result to improve the classification effect of ICTCALS segmentation method. By using KNN categorization algorithm and Naive Bayes text categorization method, it proved this way worked well on FuDan university corpus. And it also analyzed the reason why the method was relatively noneffective on the Sogou laboratory corpus through the test.
  • Keywords
    natural language processing; text analysis; Chinese text automatic categorization; ICTCLAS segmentation method; KNN categorization algorithm; Naive Bayes text categorization method; Sogou laboratory corpus; category identification capacity items; feature items; Educational institutions; Text categorization; Chinese segmentation; classification effect; high information; mix; text automatic categorization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2327-0586
  • Print_ISBN
    978-1-4673-4997-0
  • Type

    conf

  • DOI
    10.1109/ICSESS.2013.6615302
  • Filename
    6615302