• DocumentCode
    2987587
  • Title

    Chinese Review Spam Classification Using Machine Learning Method

  • Author

    Yahui Xi

  • Author_Institution
    Sch. of Manage., Tianjin Univ., Tianjin, China
  • fYear
    2012
  • fDate
    7-9 Dec. 2012
  • Firstpage
    669
  • Lastpage
    672
  • Abstract
    With great development of the e-commerce, the number of product reviews grows rapidly on the e-commerce website. Review mining has recently received a lot of attention, which aims to discover valuable information from the massive product reviews. An important subject of review mining is review spam classification, which classifies reviews into reviews or spam reviews, offering high-quality data to review mining. In this paper, we first present a categorization of Chinese review spam, and then classify the reviews by using machine learning method with different features, finally analyze the impact of different features on classification performance. The experiments show that Chinese review spam classification will obtain high accuracy by using machine learning method with appropriate features.
  • Keywords
    Web sites; data mining; electronic commerce; learning (artificial intelligence); pattern classification; unsolicited e-mail; Chinese review spam categorization; Chinese review spam classification; e-commerce Website; machine learning method; product reviews; review mining; Accuracy; Classification algorithms; Data mining; Feature extraction; Mobile handsets; Semantics; Support vector machines; Chinese review spam classification; Review mining; feature Identification; machine learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Engineering and Communication Technology (ICCECT), 2012 International Conference on
  • Conference_Location
    Liaoning
  • Print_ISBN
    978-1-4673-4499-9
  • Type

    conf

  • DOI
    10.1109/ICCECT.2012.200
  • Filename
    6414019