Applications of Data Mining Techniques in Telecom Churn Prediction

Content Provider	Semantic Scholar
Author	Umayaparvathi, V. Iyakutti, K.
Copyright Year	2012
Abstract	In this competitive world, business becomes highly saturated. Especially, the field of telecommunication faces complex challenges due to a number of vibrant competitive service providers. Therefore it has become very difficult for them to retain existing customers. Since the cost of acquiring new customers is much higher than the cost of retaining the existing customers, it is the time for the telecom industries to take necessary steps to retain the customers to stabilize their market value. This paper explores the application of data mining techniques in predicting likely churners and the impact of attribute selection on identifying the churn. It also compares the efficiency of Decision tree and Neural Network classifiers and lists their performances.
Starting Page	5
Ending Page	9
Page Count	5
File Format	PDF HTM / HTML
DOI	10.5120/5814-8122
Volume Number	42
Alternate Webpage(s)	http://research.ijcaonline.org/volume42/number20/pxc3878122.pdf
Alternate Webpage(s)	https://doi.org/10.5120/5814-8122
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article