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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/77274

    Title: Applying Data Mining Techniques to WIFLY in Customer Relationship Management
    Authors: Lin, Cheng-Jung;Chiang, Ding-An;Lai, Sheng-Wei;Wang, Yi-Hsin
    Contributors: 淡江大學資訊工程學系
    Keywords: Customer relationship management;marketing;WIFLY;clustering;churn;data mining;decision tree
    Date: 2010
    Issue Date: 2012-06-14 10:17:07 (UTC+8)
    Publisher: Faisalabad: A N S I Network
    Abstract: In recent years, wireless service subscribers are easy and frequent to change from one service provider to another for better service, which is called churn. This study applied data mining techniques to predict customer churn in Customer Relationship Management (CRM) and build predicting model to prevent customer churn. The experimental evaluation results show that customer churn model is effective and efficient. It can help enterprise in predicting the customer churn, building customer loyalty and maximizing enterprise profitability.
    Relation: Information Technology Journal 9(3), pp.488-493
    DOI: 10.3923/itj.2010.488.493
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

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