Movie Recommendations using Hybrid Recommendation Systems

Abstract

A recommendation system for movies is important in our social life due to its strength in providing enhanced entertainment. Such a system can suggest a set of movies, to users based on their interest, and personal information. Although, there are many recommendation systems present, new recommender system technologies are needed that can quickly produce high quality recommendations, even for very large-scale information resources. The proposed system has the ability to recommend movies, to a new user as well as the others by using their Facebook data. It collects all the important information, such as, popularity, liking and disliking, required for recommendation. It also takes minimal information from new user without social network login. It generates recommendations for the user based on his/her behavior on social media. This system could also be used by movie producers to get an idea about the response of their upcoming movies since all the data is extracted from the user’s behaviors.