Research on Optimization of Massive E-Commerce Data Fusion Technology

摘要

The traditional method of massive e-commerce data fusion based on the integrated averaging method is featured by high energy consumption and high total cost. Therefore, a distributed optimization technology based on distributed e-commerce data fusion is proposed in this paper. Innovating the concept of e-commerce data fusion under big data, implementing the data fusion algorithm based on the Kalman filtering method of data fusion, the massive e-commerce data fusion strategy was effectively improved by this algorithm. The effectiveness of massive e-commerce data fusion technology was verified through experimental demonstration. In the process of data fusion, it can reduce the energy consumption of the e-commerce system, save the total cost in the integration process, and improve the economic benefits of e-commerce.