Study on Category Management Model Based on Multi-Method Data Mining

Category Management is an efficient management method in the retailing, how to satisfy the consumer's requirements and how to mange the goods and promotion according to the diversity needs of consumer are the aims of this study. In this paper, the multi-method data mining (e.g.: Association, Rough Sets and Cluster.) is used to establish the category management model. Firstly, the classification model of merchandise sales based on Cluster and Rough sets is built to classify the merchandises according to the sales and to extract the characters of each category. Secondly, the restricted cross-selling products model based on the Cluster and Association is set to classify the merchandises and find the strong rules of merchandises of restricted classification. Thirdly, the Distributed store management model based on the Association and Fuzzy Cluster is designed to classify the store and provide the special promotion to different category of store. All the models increase the category management approach and improve the efficiency and accurate of the enterprises operation.