Affiliations: [a] College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China
| [b] College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China
Correspondence:
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Corresponding author. Wei Liu, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China. Tel.: +86 15063992767; Fax: +86 0532 86057875; E-mail: [email protected].
Abstract: Property insurance companies in China have accumulated certain customer resources, and these resources generate greater competitive challenges. In view of this, it is highly significant to the development of these companies to deeply analyze the individual demands of existing customers and to develop a broader cross-selling business based on the effective means of data mining tools. In this paper, the fuzzy c-means algorithm is introduced to association rules mining. Additionally, the improved Apriori algorithm-Fuzzy Association Rules Mending Apriori Algorithm based on fuzzy c-means is presented. The time complexity and space complexity of the proposed algorithm is reduced, and the application scope is expanded to uncertain environment. Furthermore, an example is given to illustrate the use of the proposed methods. With the help of data mining tools, six main valuable fuzzy association rules are mined, and one cross-selling model is built based on property insurance customers’ data sets.
Keywords: Cross-selling, data mining, customer maintenance, fuzzy association rules mending apriori algorithm
