Application of Mobile Big Data and Artificial Intelligence in the Efficiency of E-Commerce Industry

In recent years, with the rapid development of network technology and mobile clients, the upsurge of online shopping users has been accelerated. The development of e-commerce has become a key factor affecting the economy. At the same time, in the process of online shopping, users produce a large number of user access data and transaction data, which seem messy but contain huge commercial value. E-commerce urgently needs to mine its own data information and related data so as to obtain competitive advantage. Web data mining technology has become the focus of research in universities and enterprises. This paper summarizes these two methods and explains their advantages and disadvantages, respectively. Next, based on the advantages and disadvantages of model control and logic analysis, a logic analysis method based on model control is proposed. A formal analysis method combining finite machine and logic is proposed. This new method can analyze the responsibility, fairness, and timeliness of e-commerce protocol, provide a state transition diagram describing the working principle of the protocol, and fully analyze the responsibilities of all parties when repeated attacks occur. Experiments show that the efficiency of e-commerce is improved by 30%. As mentioned above, this paper hopes to play a certain role in the development of e-commerce. This paper summarizes the time series of e-commerce data, sales changes, and the sensitivity of consumer goods, which is conducive to the prediction and evaluation of the market, seize the market trend, and provide better decision-making.