• 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