Personalized Product Design Knowledge Acquisition Based on Knowledge Reduction and Knowledge Mining

Abstract

This paper makes the historical data which customers bought the products as the foundation, and suggests a method of personalized product design knowledge acquisition based on knowledge reduction and knowledge mining. Firstly, the core matrices of each specific customer group were taken as the decision variables of the decision table based on the key customer segmentation. Secondly, the knowledge reduction algorithm of Skowron discernibility matrix was use to acquire the product design information by reducing the decision table, and deleting the redundant and even product matrices that are not necessary. Thirdly, the product design information was taken as the initial data of knowledge mining, and the product design knowledge of specific customer group was obtained by a classification consistency algorithm. Finally, the stroller experimental design was taken as a case study by online interaction based on Web technology, and the conclusion of the study showed that the method was feasible.