• DocumentCode
    643914
  • Title

    Micro-blog category based on feature-words category dispersion

  • Author

    Yingyou Chen ; Qing Wu

  • Author_Institution
    Dept. of Comput., Hangzhou Dianzi Univ., Hangzhou, China
  • Volume
    01
  • fYear
    2012
  • fDate
    Oct. 30 2012-Nov. 1 2012
  • Firstpage
    105
  • Lastpage
    108
  • Abstract
    The micro-blog information classification is an important pretreatment in micro-blog data processing work. Due to the unique properties of the micro-blog text, there are some limitations when use traditional classification to deal with it. Consider to a single microblog text brief which contains less effective feature-words, and the content compare spoken of the features, this paper proposed to use similar words and collocations to extend the text feature-words, reducing the possibility of feature loss. For the feature of information selection and weight calculation, proposed one kind text classification methods which based on the feature-words category dispersion and dispersion degree. The experiments show that the propose classification method achieves good effects in the classification of micro-blog text, and has better applicability in microblog text classification scene.
  • Keywords
    Web sites; text analysis; data processing work pretreatment; dispersion degree; feature loss; feature-words category dispersion; information selection; micro-blog information classification; text classification methods; weight calculation; Accuracy; Computers; Dispersion; Support vector machine classification; Text categorization; Training; Vectors; Category dispersed; Feature-word extension; Micro-blog text classification; Term weight;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4673-1855-6
  • Type

    conf

  • DOI
    10.1109/CCIS.2012.6664377
  • Filename
    6664377