A Relationship Mining Method for E-Commerce Product Quality Characteristics based on Pattern Recognition

In order to effectively optimize product quality and control the return rate, the e-commerce platform is constructed by mining the relationship between product quality characteristics of e-commerce platforms, and then the effective verification of the method is realized through the steps of e-commerce product quality feature extraction, constraint and optimization of quality feature extraction, and application of e-commerce platform in this paper. Its experimental data shows that the return rate of “daily necessities” is 8.7 %, and the quality cost is 135,000 yuan, which obviously has quality problems, while the return rate of “home appliances” is only 2.1 %, and the quality cost is 40,000 yuan, which is the most outstanding. The results show that the application of association rule mining method can better analyze the quality characteristic relationship of e-commerce products, and provide a decision-making basis for e-commerce platforms to optimize product quality and reduce after-sales costs in the data analysis of e-commerce products.