Research on deep learning recommendation algorithm integrating user preferences
Lihong Wang · 2023
With the explosive growth of internet information and the increasing demand for service quality from users, personalized recommendations have become increasingly important. This article proposes a recommendation algorithm based on deep learning models. Utilize the powerful learning ability of deep learning models to mine more hidden information in data and fully extract features of users and projects. At the same time, in order to solve the problem of data sparsity and the dynamic change of user preferences over time, in the prediction generation stage, user preferences are integrated and updated in a timely manner. The experimental results on the dataset show that the algorithm has achieved good results in prediction accuracy and recommendation quality.