A hierarchical model of e-commerce sellers based on data mining

Abstract

This paper attempts to accurately classify e-commerce sellers based on data mining. Firstly, the original data from an e-commerce platform were preprocessed, and the classification indices were identified from five categories (products, users, traffic, sales and basic attribute). Next, the principal component analysis (PCA) and the self-organizing feature map (SOM) were fused into a hierarchical model that divides e-commerce sellers into three categories: large sellers, medium sellers and small sellers. The effectiveness of our model was verified through experiments. Finally, several operating strategies were put forward for e-commerce sellers in each category. The research results provide a good reference for the development of the e-commerce industry.