• DocumentCode
    2361863
  • Title

    A Framework of Business Intelligence-Driven Data Mining for E-business

  • Author

    Hang, Yang ; Fong, Simon

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Univ. of Macau, Macau, China
  • fYear
    2009
  • fDate
    25-27 Aug. 2009
  • Firstpage
    1964
  • Lastpage
    1970
  • Abstract
    This paper proposes a data mining methodology called Business Intelligence-driven Data Mining (BIdDM). It combines knowledge-driven data mining and method-driven data mining, and fills the gap between business intelligence knowledge and existent various data mining methods in e-Business. BIdDM contains two processes: a construction process of a four-layer framework and a data mining process. A methodology is established in setting up the four-layer framework, which is an important part in BIdDM. A case study of B2C e-Shop is provided to illustrate the use of BIdDM.
  • Keywords
    competitive intelligence; data mining; electronic commerce; business intelligence-driven data mining; e-business; knowledge-driven data mining; method-driven data mining; Bismuth; Computer networks; Data mining; Databases; Delta modulation; Information representation; Information retrieval; Information science; Internet; Knowledge representation; BI-driven Data Mining; Business intelligence; Data mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-5209-5
  • Electronic_ISBN
    978-0-7695-3769-6
  • Type

    conf

  • DOI
    10.1109/NCM.2009.403
  • Filename
    5331527