Intelligent Movie Recommendation System Based on Hybrid Recommendation Algorithms

With the continuous advancement of modern science and technology and the arrival of the artificial intelligence era, the problem of "information overload" has become increasingly prominent. The emerging recommendation systems not only provide users with an excellent user experience and convenience but also help businesses achieve greater profits. To cater to the personalized needs of users, this study has chosen a movie recommendation system based on a hybrid recommendation algorithm. This system reduces the time users spend on information searching and enhances their search efficiency, aiming to recommend movies that align with their preferences. Our hybrid recommendation algorithm has shown an accuracy rate of 81%, surpassing traditional CB, Item-Based CF, and User-Based CF algorithms. This recommendation system not only shortens the time users take to search for information but also improves their search efficiency.