• DocumentCode
    2396505
  • Title

    Text categorization based on improved Rocchio algorithm

  • Author

    Gao, Guanyu ; Guan, Shengxiao

  • Author_Institution
    Dept. of Autom., Univ. of Sci. & Technol. of China, Hefei, China
  • fYear
    2012
  • fDate
    19-20 May 2012
  • Firstpage
    2247
  • Lastpage
    2250
  • Abstract
    Text categorization is used to assign each text document to predefined categories. This paper presents a new text classification method for classifying Chinese text based on Rocchio algorithm. We firstly use the TFIDF to extract document vectors from the training documents which have been correctly categorized, and then use those document vectors to generate codebooks as classification models using the LBG and Rocchio algorithm. The codebook is then used to categorize the target documents using vector scores. We tested this method in the experiment and the result shows that this method can achieve better performance.
  • Keywords
    natural language processing; text analysis; vectors; Chinese text; LBG; TFIDF; codebooks; improved Rocchio algorithm; target documents; text categorization; text classification method; text document; training documents; vector scores; Algorithm design and analysis; Classification algorithms; Computational modeling; Support vector machine classification; Text categorization; Training data; Vectors; LBG; Rocchio Algorithm; TFIDF; Text Categorization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Informatics (ICSAI), 2012 International Conference on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4673-0198-5
  • Type

    conf

  • DOI
    10.1109/ICSAI.2012.6223499
  • Filename
    6223499