政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/70627

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政大機構典藏 > 商學院 > 企業管理學系 > 期刊論文 > Item 140.119/70627

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题名:	Discovering Recency, Frequency and Monetary (RFM) Sequential Patterns from Customers`` Purchasing Data
作者:	唐揆 Tang, Kwei
贡献者:	企管系
关键词:	Sequential pattern;Constraint-based mining;RFM;Segmentation
日期:	2009.10
上传时间:	2014-10-16 17:52:16 (UTC+8)
摘要:	In response to the thriving development in electronic commerce (EC), many on-line retailers have developed Web-based information systems to handle enormous amounts of transactions on the Internet. These systems can automatically capture data on the browsing histories and purchasing records of individual customers. This capability has motivated the development of data-mining applications. Sequential pattern mining (SPM) is a useful data-mining method to discover customers’ purchasing patterns over time. We incorporate the recency, frequency, and monetary (RFM) concept presented in the marketing literature to define the RFM sequential pattern and develop a novel algorithm for generating all RFM sequential patterns from customers’ purchasing data. Using the algorithm, we propose a pattern segmentation framework to generate valuable information on customer purchasing behavior for managerial decision-making. Extensive experiments are carried out, using synthetic datasets and a transactional dataset collected by a retail chain in Taiwan, to evaluate the proposed algorithm and empirically demonstrate the benefits of using RFM sequential patterns in analyzing customers’ purchasing data.
關聯:	Electronic Commerce Research and Applications, 8(5), 241-251
数据类型:	article
显示于类别:	[企業管理學系] 期刊論文

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