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題名 Context-based Market Basket Analysis in Multiple-Store Environment
作者 唐揆
Tang, Kwei
貢獻者 企管系
關鍵詞 Association rule; Data mining; Store chain; Algorithm
日期 2008.04
上傳時間 16-十月-2014 18:00:20 (UTC+8)
摘要 We propose a new approach to performing market basket analysis in a multiple-store and multiple-period environment. In using the method, the user first defines a time concept hierarchy and a place (location) hierarchy, according to his or her application and needs. A set of contexts is systematically derived from the two hierarchies by combining the concept levels of the two hierarchies. We developed an efficient algorithm for extracting the association rules, which meet the support and confidence requirements for all the contexts. Using the approach, a decision maker can analyze purchasing patterns at very detailed concept levels of time and place, such as a combination of days and stores, at more general levels, such as a combination of quarters and states, and combinations of detailed levels of one with general level of the other, such as a combination of days and regions. In addition to this flexibility, the association rules are well organized, because they are generated according to the contexts derived from the time and place hierarchies. A numerical evaluation shows that the algorithm is efficient in running time and may generate more specific and richer information than the store-chain rules and the traditional rules.
關聯 Decision Support Systems, 45(1), 150-163
資料類型 article
DOI http://dx.doi.org/10.1016/j.dss.2007.12.016
dc.contributor 企管系en_US
dc.creator (作者) 唐揆zh_TW
dc.creator (作者) Tang, Kweien_US
dc.date (日期) 2008.04en_US
dc.date.accessioned 16-十月-2014 18:00:20 (UTC+8)-
dc.date.available 16-十月-2014 18:00:20 (UTC+8)-
dc.date.issued (上傳時間) 16-十月-2014 18:00:20 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/70633-
dc.description.abstract (摘要) We propose a new approach to performing market basket analysis in a multiple-store and multiple-period environment. In using the method, the user first defines a time concept hierarchy and a place (location) hierarchy, according to his or her application and needs. A set of contexts is systematically derived from the two hierarchies by combining the concept levels of the two hierarchies. We developed an efficient algorithm for extracting the association rules, which meet the support and confidence requirements for all the contexts. Using the approach, a decision maker can analyze purchasing patterns at very detailed concept levels of time and place, such as a combination of days and stores, at more general levels, such as a combination of quarters and states, and combinations of detailed levels of one with general level of the other, such as a combination of days and regions. In addition to this flexibility, the association rules are well organized, because they are generated according to the contexts derived from the time and place hierarchies. A numerical evaluation shows that the algorithm is efficient in running time and may generate more specific and richer information than the store-chain rules and the traditional rules.en_US
dc.format.extent 1422904 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Decision Support Systems, 45(1), 150-163en_US
dc.subject (關鍵詞) Association rule; Data mining; Store chain; Algorithmen_US
dc.title (題名) Context-based Market Basket Analysis in Multiple-Store Environmenten_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1016/j.dss.2007.12.016en_US
dc.doi.uri (DOI) http://dx.doi.org/10.1016/j.dss.2007.12.016 en_US