• DocumentCode
    2553186
  • Title

    Hierarchical product review detection based on keyword extraction

  • Author

    Zhao Hua ; Zeng Qingtian ; Sun Bingjie ; Ni Weijian

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
  • fYear
    2012
  • fDate
    29-31 May 2012
  • Firstpage
    1299
  • Lastpage
    1302
  • Abstract
    Product reviews are very important for the sellers to make correct decisions. In order to help sellers detect the product reviews newly appearing in Internet, we propose a hierarchical product review detection method based on the keyword extraction. Taking the characteristic of the product reviews into account, this method firstly extracts the candidate keywords, and then filters out noise keywords based on the rules. And then extend these keywords based on the correlative words recognition. This paper finally realizes the hierarchical product review detection method based on these keywords. The experimental results show that the method proposed in this paper is successful.
  • Keywords
    Internet; electronic commerce; information filtering; marketing data processing; text analysis; Internet; correlative words recognition; hierarchical product review detection; keyword extraction; noise keyword filter; seller; topic detection; Computational modeling; Data mining; Dictionaries; Feature extraction; Filtering; Internet; Noise; Keyword Extraction; Product Review; Topic Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
  • Conference_Location
    Sichuan
  • Print_ISBN
    978-1-4673-0025-4
  • Type

    conf

  • DOI
    10.1109/FSKD.2012.6234340
  • Filename
    6234340