DocumentCode :
2680787
Title :
AI Based Approach of Predicting the Credit Limits of Users to Middle Customer based Mobile Communication Services
Author :
Pallegedara, A. ; Amaratunga, V.S. ; Gopura, R.A.R.C. ; Jayathileka, P.D.
Author_Institution :
Univ. of Moratuwa
fYear :
2006
fDate :
8-11 Aug. 2006
Firstpage :
588
Lastpage :
592
Abstract :
Most of the developing countries even, mobile communication has become a matter of course for many people. As markets saturate, the care and retention of existing customers becomes a key element for revenue stabilization for mobile communication network operators. We present a predictive data mining model to reduce the rate of forced churn as a consequence of non-payment: estimations of subscribers´ open amounts if being payers or non-payers allow to prevent subscribers from overspending-and ultimately churning-thus prolonging the customer relationship dwell time and securing future revenues, and hence necessary prediction system would be a great benefit to the mobile communication service providers (SP)
Keywords :
customer relationship management; data mining; invoicing; mobile communication; telecommunication services; AI based approach; charge amount estimations; credit limit prediction; customer relationship; data mining model; mobile communication services; revenue stabilization; Artificial intelligence; Artificial neural networks; Communication industry; Consumer electronics; Data mining; Information systems; Mobile communication; Predictive models; Production engineering; Subscriptions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial and Information Systems, First International Conference on
Conference_Location :
Peradeniya
Print_ISBN :
1-4244-0322-7
Type :
conf
DOI :
10.1109/ICIIS.2006.365796
Filename :
4216657
Link To Document :
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