关键词: 决策群体分类, 顾客分类, 混合数据聚类, 惩罚竞争机制

Abstract:

Customers are the decision makers in the satisfaction measurement for a product. It is significant to identify the heterogeneous features of different customer segmentations through customer classification. The primary cause of the diversity and conflict of customer evaluation characteristics is the heterogeneity of customers as decision makers. The heterogeneity of customers derives from the characteristics of customers, which includes categorical and numerical attributes simultaneously. A classification method of customers based on the punitive competition mechanism is proposed. Firstly, the initial clustering centers are determined according to the distribution regularities of the numerical and categorical attributes. Secondly, a unified similarity measurement is established and the punitive competition mechanism is introduced to realize the iteration and the auto-optimization of the number of clusters. Finally, the heterogeneous customer classification of a specific product is implemented to expound the feasibility of the proposed method. To elaborate the effectiveness of the proposed approach, the standard dataset “Heart Disease” is used to establish the comparison analysis with two classical clustering approaches K-means, and K-prototypes.

Key words: classification of decision makers, customer classification, clustering for mix-valued dataset, punitive competition mechanism