Toward Mobile Telecommunication Recommendation System through Intelligent Customers Categorization - Ghnemat, Rawan; Jaser, Edward (INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2014)
Now a day, usage of mobile devices is becoming indispensable. This is evident with current mobile penetration rates reaching 100% and even more in some countries. Customers across the world are enjoying competitive prices due to high competition among telecommunication companies. As a result of this, it is mandatory for mobile companies to provide high quality services to their customers to retain them. One aspect which will maximize customersâ€™ trust and lead to high retention rate is to offer them a suitable plan that matches their usage.Â Mobile customer usage categorization is therefore an essential task to develop intelligent business plans. Personalized recommendation system is needed to dynamically adapt the different customer behaviours with the most appropriate plan for them. In this paper we propose a new automatic approach for costumersâ€™ categorization. This will be the basis for the recommendation system. The proposed method is built using Fuzzy rule and aims at usage behaviour prediction. The rules was extracted from real customer data obtained from a leading provider. Comparison study with other categorization methods has been conducted and showed superior result and demonstrated the potential advantage of the proposed fuzzy based method.