RECOMMENDER SYSTEM

Abstract: This paper is based on a method of recommending movies to the user after assuming the priorities set/entered by the user. We now live in what some call the “era of abundance”. For any given product, there are sometimes thousands of options to choose from. Think of the examples above: streaming videos, social networking, online shopping; the list goes on. Recommender systems help to personalize a platform and help the user find something they like. The algorithm used segregates the list of movies from the dataset according to the inputs provided by user and finally displays the list of the recommended movies. The work in this project focuses on user-based collaborative filtering algorithm which is implemented in java. A bright feature of allowing the user to rate movies has also been provided in the system.