Published Paper Details:

Human behavior is mainly influenced by emotion. People are significantly impacted by the music and movies they listen and see. Video has emerged as a popular and dominant medium during this pandemic. In order to develop recommendation systems on the basis of user emotions and deliver dynamic content recommendations to users, this paper attempted to present a system design model. We will suggest the list of movies to the user by applying deep neural network technology to capture real-time emotion and combine it with conventional content-based recommendations. The term "recommender system" refers to a system that may be used to suggest products to a user based on information or criteria such as prior user comments or other user patterns. This study will offer movies or music to the user based on his or her facial expression rather than prior input from the user or any other trend. Therefore, it is important to develop a recommendation system that uses less user data while still functioning well since a user's needs could not be tied to his or her history but rather to the present, which is denoted by the user's expressions.