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.
Highlights
Cross-border e-commerce is an important part of Internet services
If users cannot search for the goods they want to buy on the platform, they will give up their willingness to purchase this time or switch to other CBEC platforms for purchase
The innovation of this paper is to study the intelligent perception system of CBEC big data decision-making based on data fusion, such as data fusion algorithm, data fusion network model, quaternion method, and big data decision intelligent perception system design experiment and CBEC user experiment, and at the same time, it is aimed at encouraging more entrepreneurs to join CBEC
Summary
Cross-border e-commerce is an important part of Internet services. With the development of the Internet, CBEC has been extended to all aspects of the economy and society, as well as its impact on the manufacturing industry, and other industries are becoming more and more important. The CBEC platform will produce a large number of data, such as user behavior data, Journal of Sensors transaction data, updated goods information, user information, and customer service information When these data are stored, there is a need for an efficient platform for data extraction and analysis. Since many main roads are equipped with drive traffic lights, it has been explored to use installed sensors as a source of traffic volume, occupancy, or speed data to inform the main road performance system With this in mind, it is possible to take advantage of the availability of mobile detector geolocation data, which include automated vehicle positioning systems for buses or taxi fleets, or mobile phones or other GPS-type equipment. The research on the decision-making of the CBEC model can help cross-border enterprises choose the right business model, reduce the possibility of decision-making mistakes, and improve the success rate of CBEC business [5]
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