MOOD -BASED MOVIE RECOMMENDATION SYSTEM

In recent years, personalized recommendation systems have become increasingly important in digital entertainment platforms. Traditional movie recommendation systems primarily rely on user history, ratings, and preferences; however, they often fail to consider the real-time emotional state of users, which significantly influences content selection. This paper presents a Movie Recommendation System Using Facial Expression Detection to provide emotion-based personalized suggestions. The proposed system captures facial expressions through a webcam and identifies emotions such as happiness, sadness, anger, and neutrality using facial recognition techniques. Based on the detected emotion, relevant movie recommendations are generated to enhance user engagement. The system is implemented using React.js for the frontend and Node.js for the backend, ensuring a fast, responsive, and user-friendly interface. This approach improves recommendation accuracy and delivers a more satisfying user experience compared to traditional methods.