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Issue title: Special Section: Recent Advances in Machine Learning and Soft Computing
Guest editors: Srikanta Patnaik
Article type: Research Article
Authors: Yan, Chuna | Sun, Haitanga | Liu, Weib; c; * | Chen, Jinb
Affiliations: [a] College of Mathematics and Systems Science, Shandong University of Science and Technology, Shandong, Qingdao, China | [b] College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China | [c] Shandong Province Key Laboratory of Wisdom Mine Information Technology, Shandong University of Science and Technology, Qingdao, China
Correspondence: [*] Corresponding author. Wei Liu, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China. Tel.: +86 15063992767; Fax: +86 053286057875; E-mail: liuwei_doctor@yeah.net.
Abstract: The analysis of lifetime value of property insurance company customers can not only help the company to allocate customer relationship management resources reasonably, save the management cost, but also help the company to identify risk timely and effectively, so that the risk control and management can be implemented. In this paper, based on RFM model, adding claim index of evaluating clients’ risk is to evaluate the lifetime value of property insurance customers quantitatively. At the same time, in view of massive uncertainties in practical decision-making, with hesitant fuzzy theory, the attributes will be weighted by hesitant fuzzy entropy. Secondly, the similarity measure theory based on hesitant fuzzy set is used to do cluster analysis and four customer homogeneous groups are obtained. Finally, calculate the lifetime value score of these four groups based on a quantitative method and analyze their characteristics from the quantitative perspective.
Keywords: Property insurance customers, customer lifetime value analysis, customer classification, hesitant fuzzy set
DOI: 10.3233/JIFS-169577
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 159-169, 2018
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