The Research Of Fuzzy Clustering Analysis And The Application In CRM

As one of Data Mining technologies, the Cluster Analysis can analyze the data without preexistent knowledge and direction. Through using the advanced algorithm appropriately, it can find the valuable information hidden in the abundant data and improve the quality of the analysis and explanation. In addition, this usage can provide the scientific judgment for subsequent data analysis and processing implement.In this paper, the basic concepts and related knowledge of clustering and fuzzy theory is presented. The principles and procedures of the clustering based on Fuzzy ISODATA are analyzed in detail. Then the clustering algorithm and program developed to realize it. This paper analyzed and studied the starting value selection method in the Fuzzy ISODATA algorithm, and used the method of maximal matrix element to ascertain the number of classification. Through the theoretical analysis and the repeated test, it optimized other parameters values in the fuzzy ISODATA algorithm. Finally, the improved fuzzy ISODATA algorithm is obtained. The algorithm reduced sensitivity to the starting value. The algorithm can highly effective clustering analyze and obtains a stable result.Customer Relationship Management (CRM) is a concept of management, also is a software system to provide the support for commercial model taking the customer as the central. In the processing of CRM, due to the differentia of customer's background, it must classify the customer based on individual request, and provide the different service to the different segmentation customers.