Intelligent Movie Recommender based on Emotions

Recommender systems are designed to help users navigate through a vast space of possible options and find the best ones that meet their needs and preferences. User state of mind and emotions are crucial for making an appropriate decision for personalization of products like music, news, and movies. In these cases, user emotions can strongly influence their overall experience and satisfaction, often more so than objective factors like plot, genre, or ratings. Recognizing the importance of user emotions, modern recommender systems have begun incorporating emotional analysis techniques into their algorithms. These techniques can help the system better understand and capture the emotional states of users, which in turn allows for more accurate and personalized recommendations.