Abstract

Customer information is critical to customer relationship management. The goal of this research is to improve the efficiency of customer relationship management through developing a customer information system. Fuzzy terms with linguistic variables can help specific queries to be more versatile and user friendly for customer data mining. In this paper, we propose a method integrating cluster analysis with linguistic variables in the context of fuzzy query logistics. Based on the proposed method, we constructed a customer information system that can offer the user useful information as regards with strategy, decision making, and better resource allocation methods. We expect to decrease total execution time and to increase the practicability with the feature of customer information cluster analysis.

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