Research on user interest prediction and recommendation algorithm based on artificial intelligence algorithm

This is the authors' abstract. We don't add key points for this paper.

With the development of the Internet, more and more data are generated by users on the network, and the interests of users are becoming more and more diverse. How to predict the user's interest according to the user's behavior data and recommend relevant content to the user has become a hot research direction in the Internet field. In this paper, "Research on User interest prediction and recommendation Algorithm based on artificial intelligence algorithm", the user interest prediction and recommendation algorithm is deeply studied and discussed. Firstly, this paper summarizes and analyzes the relevant algorithms of user interest prediction. Traditional user interest prediction algorithms are mainly modeled based on user behavior data and content characteristics, such as collaborative filtering algorithm and content-based recommendation algorithm. However, these algorithms have certain limitations when dealing with massive data and diverse user interests, so it is necessary to introduce artificial intelligence algorithms to improve prediction accuracy and recommendation effect. Secondly, this paper proposes a solution based on artificial intelligence algorithm for user interest prediction and recommendation. Firstly, feature extraction and representation learning of user behavior data are carried out by deep learning algorithm, so as to achieve accurate prediction of user interest. Secondly, the model algorithm is used to optimize the decision-making strategy of the recommendation system, so as to improve the personalization and accuracy of the recommendation. By introducing artificial intelligence algorithm, hidden information in user behavior data can be better mined, and the accuracy and effect of user interest prediction and recommendation can be improved. Finally, this paper verifies the effectiveness of the user interest prediction and recommendation algorithm based on artificial intelligence through experiments. The experimental results show that the introduction of artificial intelligence algorithm can significantly improve the accuracy and effect of user interest prediction and recommendation, which is of great significance for improving the user experience and business value of the recommendation system.