Abstract: Recommender system is one of the recent applications which help to recommend the items or products based on the user needs. Since the user needs varies from person to person we cannot generalize the recommender system. Movie recommender system also has the same issues since individuals have different expectations while watching a movie and recommendation is not possible based on the annotations given by the other users. To overcome this situation an affective recommender framework is proposed in this work. One of the most famous methodology is collaborative filtering and finding the some top similar users and then find the movies those users has viewed and given a good rating which has not been viewed by particular user, recommending movies to user has great benefit, but applying probability for particular movie based on genre is done, which will increase accuracy in recommendation engine.
Keywords: Recommender system, Movie recommender system, Rating and Genre.