An intelligent recommendation system and method for industrial Internet platform

In recent years, with the rise of the industrial Internet, more and more industrial Internet platforms have gradually emerged. The large amount of information on the industrial Internet platform makes it difficult for users to query relevant information that suits them. This is the information overload problem of the platform. The recommendation system is an effective method to effectively solve the information overload. This paper proposes a recommendation system for the industrial Internet platform, and designs a recommendation system and method for the industrial Internet platform based on convolutional neural network and attention mechanism combined with factorization machine. At the same time, it also solves the pain points of different importance of a certain product or information to different enterprise users according to the characteristics of the industrial Internet platform.