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    題名: Combing customer profiles for members' return visit rate predictions
    作者: Chen, Chun-Hao;Chiang, Rui-Dong;Wong, Yi-Hsin;Chu, Huan-Chen
    貢獻者: 淡江大學資訊工程學系
    關鍵詞: Behavioral targeting;Customer profile;Concept drift
    日期: 2013-02
    上傳時間: 2013-10-16 15:24:39 (UTC+8)
    出版者: Kumamoto: ICIC International
    摘要: The major profit of companies in Taiwan is generated by online advertising and e-commerce. Effective advertising requires predicting how a user responds to an advertisement and then targeting (presenting the advertisement) to reflect users’ favor. As customers’ preferences may change over time, we take the different types of past behavior patterns of the registered members to capture concept drifts. Then, we combine the click preference index (CPI) and the preference drifts to propose a Behavioral Preference (BP) model, and to predict the members’ return visit rates in the specific category of the portal site. The marketers of the portal site can target the registered members with high return visit rates and design corresponding marketing strategies. The experimental results with a real dataset show that our model can effectively predict the registered members’ return visit rates.
    關聯: International Journal of Innovative Computing, Information and Control 9(2), pp.503-523
    DOI: 
    顯示於類別:[資訊工程學系暨研究所] 期刊論文

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