A Multi-Criteria Movie Recommendation System based on User Preferences and Movie Features

In this research, we develop a multi-criteria movie recommendation system that provides personalised recommendations by taking into consideration both user preferences and aspects. To get over each method's specific drawbacks, the suggested takes hybrid approach combines collaborative filtering with content-based techniques. The uses to capture based on historical ratings, while methods analyze features such as genre, director, actors, keywords enhance process. Additionally, integrate various external data sources like reviews, social media sentiment, box office performance enrich feature set. employs weighted aggregation method combine these criteria generate comprehensive score. effectiveness of proposed is evaluated utilizing standard metrics including recall, precision, F1-score publicly available dataset. results demonstrate our effectively captures more accurate diverse compared traditional single-criterion approaches.