Discovering recency, frequency, and monetary (RFM) sequential patterns from customers' purchasing data

NCU Institutional Repository > 管理學院 > 資訊管理研究所 > 期刊論文 > Item 987654321/29656

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/29656

题名:	Discovering recency, frequency, and monetary (RFM) sequential patterns from customers' purchasing data
作者:	Chen,YL;Kuo,MH;Wu,SY;Tang,K
贡献者:	資訊管理研究所
关键词:	MULTIPLE-STORE ENVIRONMENT;MARKET BASKET ANALYSIS;DATABASES;SEQUENCES;KNOWLEDGE
日期:	2009
上传时间:	2010-06-29 20:37:29 (UTC+8)
出版者:	中央大學
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 de. ne 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. (c) 2009 Elsevier B.V. All rights reserved.
關聯:	ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS
显示于类别:	[資訊管理研究所] 期刊論文

文件中的档案:

档案	描述	大小	格式	浏览次数
index.html		0Kb	HTML	967	检视/开启

在NCUIR中所有的数据项都受到原著作权保护.

社群 sharing

数据加载中.....