DocumentCode
2863995
Title
GSM Churn Management Using an Adaptive Neuro-Fuzzy Inference System
Author
Karahoca, Adem ; Karahoca, Dilek ; Aydin, Nizamettin
Author_Institution
Bahcesehir Univ., Istanbul
fYear
2007
fDate
11-13 Oct. 2007
Firstpage
323
Lastpage
326
Abstract
The movement of subscribers from one operator to another operator is named as churn management for looking for better and cheaper products and services. As markets become saturated and competition intensifies, customers have more choices to take promotions from alternative telecom operators in Turkish GSM (global services of mobile communications) sector. This study compares various data mining techniques to obtain best practical solution for churning customer detection. Test results offer the adaptive neuro fuzzy inference system (ANFIS) as a means to efficient churn management methodology. The test bed results show that ANFIS provides 85% of sensitivity with 88% of specificity where it classified 80% of the instances correctly.
Keywords
adaptive systems; cellular radio; customer satisfaction; data mining; fuzzy neural nets; fuzzy reasoning; telecommunication services; GSM churn management; Turkish GSM sector; adaptive neuro-fuzzy inference system; churning customer detection; data mining techniques; Adaptive systems; Cellular neural networks; Costs; Customer service; Data mining; Demography; GSM; Pervasive computing; Predictive models; Telecommunications;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Pervasive Computing, 2007. IPC. The 2007 International Conference on
Conference_Location
Jeju City
Print_ISBN
978-0-7695-3006-2
Type
conf
DOI
10.1109/IPC.2007.119
Filename
4438449
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