GSM churn management using an adaptive neuro-fuzzy inference system

Adem Karahoca; Dilek Karahoca; Nizamettin Aydin

doi:10.1109/IPC.2007.119

GSM churn management using an adaptive neuro-fuzzy inference system

Adem Karahoca^*, Dilek Karahoca, Nizamettin Aydin

^*Corresponding author for this work

Bahcesehir University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007
Pages	323-326
Number of pages	4
DOIs	https://doi.org/10.1109/IPC.2007.119
Publication status	Published - 2007
Externally published	Yes
Event	2007 International Conference on Intelligent Pervasive Computing, IPC 2007 - Jeju Island, Korea, Republic of Duration: 11 Oct 2007 → 13 Oct 2007

Publication series

Name	Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007

Conference

Conference	2007 International Conference on Intelligent Pervasive Computing, IPC 2007
Country/Territory	Korea, Republic of
City	Jeju Island
Period	11/10/07 → 13/10/07

Access to Document

10.1109/IPC.2007.119

Cite this

Karahoca, A., Karahoca, D., & Aydin, N. (2007). GSM churn management using an adaptive neuro-fuzzy inference system. In Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007 (pp. 323-326). Article 4438449 (Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007). https://doi.org/10.1109/IPC.2007.119

@inproceedings{94902828319345e4a1a549be0e942f82,

title = "GSM churn management using an adaptive neuro-fuzzy inference system",

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.",

author = "Adem Karahoca and Dilek Karahoca and Nizamettin Aydin",

year = "2007",

doi = "10.1109/IPC.2007.119",

language = "English",

isbn = "0769530060",

series = "Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007",

pages = "323--326",

booktitle = "Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007",

note = "2007 International Conference on Intelligent Pervasive Computing, IPC 2007 ; Conference date: 11-10-2007 Through 13-10-2007",

}

Karahoca, A, Karahoca, D & Aydin, N 2007, GSM churn management using an adaptive neuro-fuzzy inference system. in Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007., 4438449, Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007, pp. 323-326, 2007 International Conference on Intelligent Pervasive Computing, IPC 2007, Jeju Island, Korea, Republic of, 11/10/07. https://doi.org/10.1109/IPC.2007.119

GSM churn management using an adaptive neuro-fuzzy inference system. / Karahoca, Adem; Karahoca, Dilek; Aydin, Nizamettin.
Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007. 2007. p. 323-326 4438449 (Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

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T2 - 2007 International Conference on Intelligent Pervasive Computing, IPC 2007

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ER -

GSM churn management using an adaptive neuro-fuzzy inference system

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