Recommender System for Telecommunication Industries: A Case of Zambia Telecoms
A Recommender System for Telecommunication companies using call detail reports (CDR’s), machine learning algorithms and big data concepts is described.
Abstract
Recommender systems use machine learning algorithms and artificial intelligence techniques to recommend products to customers. These algorithms use historical data of purchases of other people to determine which products to recommend to a particular customer, in general recommender systems are designed in such a way that they automatically generate personalized suggestions of products to customers. With the competitiveness that is growing in the Zambian telecom industry as a result of the new fourth mobile telecom service provider, telecommunication operators are looking for ways of attracting and keeping their subscribers on their network by giving affordable products to their subscribers. This research paper describes a Recommender System for Telecommunication companies using call detail reports (CDR’s), machine learning algorithms and big data concepts.