Publication

Abstract : One of the best forms of entertainment today is online multimedia with movies and various other entertainment sources at the tip of our fingers. However, finding a movie from the numerous options available in a movie database to suit a user's taste is a non-trivial task. Most recommendation systems do not consider the user's limitations, such as whether the user has the means to watch the movie suggested by the system. This paper proposes a system to provide recommendations that are platform specific. Two sources of movies have been considered, viz., Netflix and Amazon Prime, and other data sets can be included as well. In addition to providing recommendations, the proposed system helps filter movies based on user-specified criteria. It applies big data analytics for faster execution of both movie recommendation and data filtering and can work with large and distributed movie databases.