MOVIE RECOMMENDER SYSTEM USING CONVOLUTIONAL NEURAL NETWORKS ALGORITHM

Abstract

In streaming platforms, recommendation algorithms play a crucial role in recommending content. For streaming movie services such as Netflix, recommendation algorithms are crucial for assisting consumers in discovering new films to watch. Thus, in this paper, we present a deep learning strategy based on Convolutional Neural Networks (CNN) to generate a collaborative filtering system that predicts a user's movie rating using a big database of ratings from other users. The findings that were achieved by the Movie Recommendation System utilizing CNNs on the MovieLens 100k dataset highlight the usefulness of CNNs in capturing the complex and non-linear interactions that occur between users and movies.