Movie Recommendation System using RNN Approach

Abstract

The problem of information overload has been made worse by the quick advancement of information technology and the quick expansion of the Internet. In response to this issue, recommender systems have developed, assisting users in finding relevant material. The study of personalized recommendation services has seen a change in focus as a result of the complexity of the social setting. We present a novel recommendation approach based on social network recurrent neural network in order to address the sparsity problem of recommender systems while enhancing their accuracy and diversity in complicated scenarios. Using this approach, we group users and take a number of intricate criteria into account.