• DocumentCode
    2933975
  • Title

    Finer Granularity Clustering for Opinion Mining

  • Author

    Luo, Yin ; Lin, Gongqi ; Fu, Yan

  • Author_Institution
    Dept. of Software, Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • Volume
    1
  • fYear
    2009
  • fDate
    12-14 Dec. 2009
  • Firstpage
    68
  • Lastpage
    71
  • Abstract
    The boom of opinion-rich resources such as online review Websites, discussion groups, personal blogs and forums on the Web has attracted many research efforts on opinion mining. Positive and negative opinions represented in review documents are helpful information for governments to improve their services, for companies to market their products, and for customers to purchase their commodities. In this paper, we introduce a new approach that employs finer granularity clustering for opinions extraction and clustering for the calculation of their sentiment orientation of opinions. The experimental result shows that the approach is qualitatively quite useful when used to analyze the netizens´ opinions to hot topics from some Websites.
  • Keywords
    Web sites; data mining; text analysis; discussion groups; finer granularity clustering; forums; online review Websites; opinion mining; opinion-rich resources; personal blogs; Blogs; Computational intelligence; Computer science; Consumer electronics; Data mining; Design engineering; Government; Humans; Information retrieval; Natural languages; Semantic Orientation; Text mining; finer granularity clustering; opinion mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-0-7695-3865-5
  • Type

    conf

  • DOI
    10.1109/ISCID.2009.24
  • Filename
    5370398