Intelligent Perception System of Big Data Decision in Cross-Border e-Commerce Based on Data Fusion

Abstract

There is a gap between supply and demand in cross-border e-trading platforms. The so-called supply and demand gap refers to the existing good companies that cannot meet the needs of buyers. Cross-border e-commerce, the buyer’s purchase demand is often included in the buyer’s behavior, such as searching for goods by pressing buttons, clicking price, category and other means, and on-site delivery time. It is important for CBEC to analyze the buyer’s needs to protect the procurement and provide the seller with reference to supply, so as to solve the supply and demand gap between the buyer and the seller. This paper mainly studies the CBEC big data decision intelligent perception system based on data fusion. It is the same as the innovation process of better application of data fusion to the e-commerce business model. At the same time, the key technologies of data extraction, conversion, data warehouse, and front-end display in the system construction are analyzed and designed. This paper mainly uses data fusion algorithm, data fusion network model, quaternion method, big data decision intelligent sensing system framework design experiment, and CBEC user experiment to study the CBEC big data decision intelligent sensing system based on data fusion, and also with the development of CBEC, I hope more people can participate in CBEC practice. The results show that with the increase of data volume of the CBEC platform from 2016 to 2020, the construction of the CBEC platform business of big data production intelligent perception system considers the situation of users from seven aspects. With the increase of consumption, domestic consumers are increasingly pursuing a better life, cross-border import e-commerce ushered in a great development era.