E-Commerce Commodity Recommendation System Based on Social Perception and Mobile Computing

With the continuous progress of personalized recommendations, it is difficult for consumers to access product information that is different from their own interests and preferences. This paper combines social perception and mobile computing to improve the e-commerce product recommendation algorithm and combine social network to perform consumer data perception to improve the effect of personalized recommendation. Moreover, this paper builds an e-commerce product recommendation system with the support of improved algorithms and launches experiments through simulation. In addition, this paper designs an experiment to evaluate the data perception effect of an e-commerce product recommendation system based on social perception and mobile computing. Through the results of experimental research, it can be seen that the e-commerce product recommendation system based on social perception and mobile computing proposed in this paper can effectively improve the accuracy of product recommendation and improve customer shopping experience.