• DocumentCode
    3439434
  • Title

    A Framework of Review Analysis for Enhancement of Business Decision Making

  • Author

    Qazi, Atika ; Raj, Raghu G. ; Tahir, M. ; Naqvi, Syed Ghaour Abbas

  • Author_Institution
    Univ. of Malaya, Kuala Lumpur, Malaysia
  • fYear
    2013
  • fDate
    7-10 Dec. 2013
  • Firstpage
    955
  • Lastpage
    958
  • Abstract
    In order to remain competitive, modern businesses must keep informed about consumers´ opinions via web-based reviews or similar channels. Today, the usefulness factor in opinion mining is mainly achieved through helpful user ratings in reviews. Reviews belong to different categories and each category contains different types of information that have not yet been the focus of sentiment analysis research so far. There is useful content in each type of review that may be helpful to users as well as designers. Therefore, it is essential to classify reviews into multiple types and then share relevant information with people involved in the development of business products and services. We hereby propose a review analysis framework, which may help designers and customers to extract useful information from user-generated contents. The proposed framework aims to enable users, designers and potential buyers to enhance decision making strategies and, hence, and improve business intelligence.
  • Keywords
    Internet; competitive intelligence; data mining; decision making; reviews; Web; business decision making enhancement; business intelligence improvement; business products; business services; opinion mining; review analysis framework; sentiment analysis research; user ratings; user-generated contents; Computational linguistics; Conferences; Data mining; Decision making; Motion pictures; Pragmatics; Business Intelligence; Opinion Mining; Review Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on
  • Conference_Location
    Dallas, TX
  • Print_ISBN
    978-1-4799-3143-9
  • Type

    conf

  • DOI
    10.1109/ICDMW.2013.160
  • Filename
    6754024