Using Data Mining in Customer Relationship Management (Case Study of the Insurance Industry)

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Khalilpour Darzi, Mohammad Rasoul | 2018

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 51246 (01)
University: Sharif University of Technology
Department: Industrial Engineering
Advisor(s): Akhavan Niaki, Taghi; Khedmati, Majid
Abstract:
This paper presents some approaches based on data mining techniques to solve the prediction task of Computational Intelligence and Learning (CoIL) Challenge 2000. The prediction task of the contest is a direct mailing problem and the goal is to improve its response rate. The main issue in this competition is the incompatibility of the dataset in which the distribution of the classes of the target attribute is highly unbalanced. This in turn causes high error rate in identifying the minority class samples. Three different level methods including data-level, algorithm-level, and hybrid method are used to overcome this issue. The specificity and sensitivity criteria are employed to compare the performance of the methods. Among the methods proposed in this paper, the best one performs much better than the winner of the competition
Keywords:
Data Mining ; Classification ; Insurance ; Sampling ; Customer Relationship Management ; Cost-Sensitive Learning ; Direct Mail

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