Applying Data Mining Techniques to WIFLY in Customer Relationship Management

機構典藏 > College of Engineering > Graduate Institute & Department of Computer Science and Information Engineering > Journal Article > Item 987654321/77274

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/77274

Title:	Applying Data Mining Techniques to WIFLY in Customer Relationship Management
Authors:	Lin, Cheng-Jung;Chiang, Ding-An;Lai, Sheng-Wei;Wang, Yi-Hsin
Contributors:	淡江大學資訊工程學系
Keywords:	Customer relationship management;marketing;WIFLY;clustering;churn;data mining;decision tree
Date:	2010
Issue Date:	2012-06-14 10:17:07 (UTC+8)
Publisher:	Faisalabad: A N S I Network
Abstract:	In recent years, wireless service subscribers are easy and frequent to change from one service provider to another for better service, which is called churn. This study applied data mining techniques to predict customer churn in Customer Relationship Management (CRM) and build predicting model to prevent customer churn. The experimental evaluation results show that customer churn model is effective and efficient. It can help enterprise in predicting the customer churn, building customer loyalty and maximizing enterprise profitability.
Relation:	Information Technology Journal 9(3), pp.488-493
DOI:	10.3923/itj.2010.488.493
Appears in Collections:	[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

Files in This Item:

File	Description	Size	Format
1812-5638_9(3)p488-493.pdf		1100Kb	Adobe PDF	357	View/Open