A Hybrid Movie Recommender System and Rating Prediction Model

In the current era, a rapid increase in data volume produces redundant information on internet. This predicts appropriate items for users great challenge systems. As result, recommender systems have emerged this decade to resolve such problems. Various e-commerce platforms as Amazon and Netflix prefer using some decent recommend their users. literature, multiple methods matrix factorization collaborative filtering exist been implemented long time, however recent studies show that other approaches, especially artificial neural networks, promising improvements area of research. research, we propose new hybrid system results better performance. proposed system, are divided into two main categories, namely average users, non-average Then, various machine learning deep applied within these categories achieve results. Some decision trees, support vector regression, random forest On side, factorization, filtering, approach achieves compared traditional methods.