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    政大機構典藏 > 商學院 > 企業管理學系 > 期刊論文 >  Item 140.119/10254
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/10254

    Title: Market basket analysis in a multiple store environment
    Authors: Chen, Yen-Liang;Tang, Kwei;Shen, Ren-Jie;Hua, Ya-Han
    Keywords: Association rules;Data mining;Store chain;Algorithm
    Date: 2005-08
    Issue Date: 2008-11-25 10:41:18 (UTC+8)
    Abstract: Market basket analysis (also known as association-rule mining) is a useful method of discovering customer purchasing patterns by extracting associations or co-occurrences from stores' transactional databases. Because the information obtained from the analysis can be used in forming marketing, sales, service, and operation strategies, it has drawn increased research interest. The existing methods, however, may fail to discover important purchasing patterns in a multi-store environment, because of an implicit assumption that products under consideration are on shelf all the time across all stores. In this paper, we propose a new method to overcome this weakness. Our empirical evaluation shows that the proposed method is computationally efficient, and that it has advantage over the traditional method when stores are diverse in size, product mix changes rapidly over time, and larger numbers of stores and periods are considered.
    Relation: Decision Support Systems

    Volume 40, Issue 2, August 2005, Pages 339–354
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1016/j.dss.2004.04.009
    DOI: 10.1016/j.dss.2004.04.009
    Appears in Collections:[企業管理學系] 期刊論文

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