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It is known that the collection of the specific needs of mobile users and location management in an electronic commerce recommendation system are important indicators used to evaluate user satisfaction and system execution efficiency. In order to improve the low accuracy of recommendation systems and ensure real-time location management, we proposed cooperative embedded data collection and control of the electronic commerce recommendation system for mobile crowd system. First of all, we would assign every user with a mobile crowd terminal. The terminal could collect the user’s demand and personalized data. An embedded terminal could provide users with a real-time, accurate, personalized shopping experience. The terminal could collect the user demand dynamic evolution function. Then, the electronic commerce recommendation application platform would be formed through the deployment of a mobile crowd terminal. The platform collects and forwards the signal acquisition through a single port, dual port and port more adaptive network structure. Experimental results show that the performance of the proposed scheme is superior to the electronic commerce recommendation system based on user personalization drive, such as the data collection of the embedded crowd terminal delay, precision and accuracy of electronic commerce recommendation, as well as the number of iterations. The proposed scheme is more suitable for an electronic commerce recommendation system.

Electronic commerce recommendation mobile crowd system based on cooperative data collection and embedded control