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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/94406

    Title: 超市賣場推薦系統實作
    Other Titles: Design of supermarket recommender system
    Authors: 張淑俐;Chang, Shu-Li
    Contributors: 淡江大學資訊工程學系碩士在職專班
    蔣璿東;Chiang, Rui-Dong
    Keywords: 推薦系統;協同過濾;Recommender System;Collaborative Filtering
    Date: 2013
    Issue Date: 2014-01-23 14:35:30 (UTC+8)
    Abstract: 近年來因電子商務的興起,人們的消費型態也從傳統的實體店面購物,轉變為在網路商店上進行消費,推薦系統在電子商務上的運用很多,也有一定之成效,但對於實體零售業(Retail)而言,由於商家對於顧客消費並沒有設定門檻,無論是不是會員都可以進行商品購買,所以,商家只能針對會員的消費行為進行分析,但對於非會員的部份,卻無法有效掌握。
    Due to the rise of e-commerce in recent years, people’s consumption patterns have also changed from traditional physical storefront shopping to online shopping consumption. However, TRhe recommender system has a lot of applications in e-commerce and has also had some measure of success, but in physical retail, business firms never set the threshold for consumer spending and disregard whether or not members are able to purchase goods. Thus, business firms can only analyze members’ consumer behavior, but as non-members cannot be effectively controlled.

    This research on the conceptual application of the recommender system in physical retail was conducted using the item-based method often seen in collaborative filtering, and the feasibility of indiscriminately applying the recommender system in the small categories of recommended commodities was evaluated. We use a well-known enterprise data operations provided experimental data sets,it is hoped that the sales of the commodities can be strengthened with the help of the recommender system, thereby generating consumers’ reliance, improving the degree of loyalty, and reducing the loss o f customers. In terms of the manufacturers, all the categories of consumers’ purchases can also be even more effectively grasped, and the common marketing, information cross-application, product integration, and other marketing strategies will increase consumers’ subsequent purchase possibilities, attract and keep customers, and increase the market share.

    Therefore, the recommendation methods of this research can adequately provide retail a basis for marketing analysis, transform consumption patterns and thinking, and enable members to exactly obtain the appropriate recommendations, thus strengthening supermarkets’ operations and profits.
    Appears in Collections:[資訊工程學系暨研究所] 學位論文

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