• DocumentCode
    496824
  • Title

    Application of Fuzzy-C-Means Algorithm Based on Rough Set in Client Subdivision Research

  • Author

    Wang, Jing ; Fang, Niu Gai ; Sun, Qingyu

  • Author_Institution
    Dept. of the Libr., Hebei Univ. of Eng., Handan, China
  • Volume
    1
  • fYear
    2009
  • fDate
    18-19 July 2009
  • Firstpage
    28
  • Lastpage
    31
  • Abstract
    In an increasingly competitive market, the management of client relationship is becoming a key point for a enterprise to get a success in the competition, client subdivision is a foundation for the enterprise to make a precise marketing strategy and a successful management of client group, based on the development of data mining technology, a fuzzy-C-means(FCM) algorithm model is founded to do the client subdivision in this paper, Selecting the rough set (RS) to make a reduction to the redundancy attributes of the sample, thus reducing the dimensions of the sample input space, at a certain extent improved the accuracy and the classify effect of this algorithm, through analyses the clustering results, we provide a quantitative basis for the enterprise in the proceeding of making a marketing strategy, enhanced the pertinency and efficiency of the enterprise marketing activities.
  • Keywords
    data mining; fuzzy set theory; marketing data processing; rough set theory; client subdivision research; data mining; fuzzy-C-means algorithm; marketing strategy; rough set theory; Algorithm design and analysis; Clustering algorithms; Conference management; Engineering management; Fuzzy set theory; Information analysis; Marketing management; Research and development management; Resource management; Technology management; client subdivision; fuzzy-c-means algorithm; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-0-7695-3699-6
  • Type

    conf

  • DOI
    10.1109/APCIP.2009.15
  • Filename
    5196987