• DocumentCode
    2408147
  • Title

    Business Stakeholder Analyzer: An Automatic Classification Approach to Facilitating Collaborative Commerce on the Web

  • Author

    Chung, Wingyan

  • Author_Institution
    The University of Texas at El Paso
  • fYear
    2005
  • fDate
    03-06 Jan. 2005
  • Abstract
    As the Web is used increasingly to share and disseminate information, business analysts and managers are challenged to understand stakeholder relationships. Traditional stakeholder analysis approaches fail to accommodate the rapid Web growth while existing business intelligence tools lack analysis capability. This paper proposes an automatic classification approach to business stakeholder analysis on the Web. Based on the approach, we developed a system called Business Stakeholder Analyzer to perform automatic classification of stakeholder types. Experimental results showed that, compared with humans, the system achieved better within-class accuracies in widespread stakeholder types such as "partner/sponsor/supplier" and "media/reviewer." It was more efficient than human classification. The encouraging findings suggest a promising future of our approach to facilitating knowledge sharing in collaborative commerce.
  • Keywords
    Support Vector Machines; Web page classification; business intelligence; feature selection; neural network; stakeholder analysis; Business; Collaboration; Companies; Educational institutions; Failure analysis; Humans; Information analysis; Intelligent networks; Performance analysis; Web pages;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Sciences, 2005. HICSS '05. Proceedings of the 38th Annual Hawaii International Conference on
  • ISSN
    1530-1605
  • Print_ISBN
    0-7695-2268-8
  • Type

    conf

  • DOI
    10.1109/HICSS.2005.134
  • Filename
    1385256