Research on Recommendation System Algorithm Based on Deep Learning Mode in Grid Environment

In order to effectively improve the accuracy of recommending information for users, this paper introduces the deep learning mode by means of grid environment, and proposes a recommendation system algorithm based on deep learning mode in grid environment. Firstly, the advantages and disadvantages of content recommendation and collaborative filtering recommendation algorithms are analyzed. Then, the deep learning mode is introduced, the recommended environment framework is established in the grid environment, and the recommendation algorithm is optimized. Finally, the simulation results show that the proposed recommendation algorithm can quickly establish a user recommendation list and effectively improve the recommendation accuracy.