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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/52385

    Title: Analyzing behaviors of WIFLY customers using data mining techniques
    Other Titles: 資料探勘技術於WIFLY客戶行為模式之研究
    Authors: 林正榮;Lin, Cheng-jung
    Contributors: 淡江大學資訊工程學系博士班
    蔣定安;Chiang, Ding-an
    Keywords: 顧客關係管理;資料探勘;群集;決策樹;流失(保留);Customer Relationship Management;data mining;Clustering;Decision tree;Churn
    Date: 2010
    Issue Date: 2010-09-23 17:35:29 (UTC+8)
    Abstract: 隨著通訊技術的演進, 網際網路的蓬勃發展,過去以個人電腦以及區域網路技術所主導的網際網路形態逐步轉變為通訊、娛樂、電子商務主導的網際網路型態。不再受限於有線網路連結環境的限制,透過上網熱點的連結,使得無線網路的連結更具有便利及即時性質,而多元化的時空網路連結環境使得網際網路的運用更具備實用及商業價值。

    WIFLY建構於台北市,採用Wi-Fi無線網路為基礎網路架構,因取得World Teleport Association, WTA旗下的Intelligent Community Forum 所頒發的智慧城市首獎,並獲得國際認證機構JiWire評定為全球最大之無線寬頻網路城市,在2006年成為全球最大公共無線寬頻網路城市。


    As communication techniques improve, Internet continues to boom. Internet leading shape gradually shifted focus from personal computer and local area network for Internet service to these used in communications, recreation, e-commerce etc. Because of wireless networks is not restricted the wired networks link environment, while broadband speeds up Internet connectivity, the wireless ratio-based networks known as Wi-Fi service untether it through hotspots to link Internet. Hence, wireless network is not only more convenient and immediate properties, but also possesses practical and commercial value.

    WIFLY is a Wi-Fi service infrastructure in Taipei city, which has begun since December 20 of 2005. The Intelligent Community Forum named Taipei city as recipient of its 2006 Intelligent Community Forum of the year award and presented awards to the Intelligent Building of the year, Intelligent Community Technology and Intelligent Community Visionary of the Year as well Taipei is on the way to develop a stable wireless city following the completions of many of its related infrastructure. JiWire assessed the Taipei is the global largest city of wireless broadband network.

    In recent years, the guidance of customer relationship management between enterprises and customers gradually evolved from people into product. There is huge competition for wireless networks operators. As Internet subscribers in wireless networks field are continually growing, wireless network operators have to understand the rising consumer demand and develop suitable strategies, critical to attracting repeat customers, consolidate customers loyalty and satisfaction, with continually prospects new clients etc., Therefore, the marketing strategy and CRM are becoming very important.

    This dissertation applied data mining techniques to analyze WIFLY users’ behavior, and identifies the significant value of WIFLY subscribers to predict customer churn in 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.
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

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