A novel cluster algorithm for telecom customer segmentation

With the rapid development of the telecom market, telecom customer gradually shows the characteristics of differentiation and diversification. Telecom customer clustering is an effective method for marketing and retention. In this paper, we propose a cluster algorithm based on k-means and Multivariable Quantum Shuffled Frog Leaping Algorithm (MQSFLA), called MQSFLA-k, which can be used as a customer segmentation method in telecom customers marketing. Simulation results show that the proposed MQSFLA has advantages of both convergence rate and convergence accurate value compared with other intelligent algorithms. In addition, the proposed MQSFLA based MQSFLA-k has the advantage of convergence rate compared with k-means. Furthermore, MQSFLA-k can solve the problem of telecom customer segmentation effectively, which provides target customers for retention.

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