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Paper Information

Journal:   MANAGEMENT RESEARCH IN IRAN (MODARES HUMAN SCIENCES)   SUMMER 2012 , Volume 16 , Number 2 (75); Page(s) 57 To 71.
 
Paper: 

CLASSIFICATION OF MOBILE BANKING USERS BY DATA MINING APPROACH: COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORKS AND NAIVE BAYES TECHNIQUES

 
 
Author(s):  HASSANZADEH ALIREZA*, GHANBARI MOHAMMAD HESAM, ELAHI SHAABAN
 
* FACULTY OF MANAGEMENT AND ECONOMICS, TARBIAT MODARES UNIVERSITY, TEHRAN, IRAN
 
Abstract: 

In recent decade, development of different technologies is dramitically high that has influenced services. One of the fields affected from information technology is bankining industry. Wireless technology is one of the many fields of information technology that have a greate development in the recent years; one of its results is mobile banking service. Banking industry is a smple that uses data mining technique. Data mining is a kind of exploring knowledge to solve a special problem. In this research, 232817 data have been used to find some models by artificial neural networks and naive bayes technique in according to customers' attributes. Furtheremore, the results of this research help to classify customers who use mobile banking service. Then the bank can offer the service to those who is in this classification but do not use this service. So the bank can attract more customers, maintain its customers, and keep high customers' satisfaction. Also, in this way, it is possible that using this service, by the targeted customers, encourage others to use this service. This research revealed that artificial neural networks is more accurate than naivie bayes approach (it s about 0.5%) and the research's hypothesis is proved.

 
Keyword(s): MOBILE BANKING, DATA MINING, ARTIFICIAL NEURAL NETWORKS, NAIVE BAYES, RAPID MINER
 
References: 
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