Paper Title:MOVIEREC: A Case study on Movie based Recommender


MOVIEREC was created for moviegoers who want to find movies of their taste. A moviegoer may have to spend a lot of time on the web reading and watching reviews to reach a conclusion as to whether he/she should watch a movie or not. Usually the information available in various media about the movies are not targeted towards user’s taste , or may display the information which may not always stay on the topic and slowly drift away from the viewer’s interests. MOVIEREC involves taking the user’s feedback and finding similarity of the user to other users by using collaborative filtering and clustering algorithms. These algorithms, based on the user’s feedback, place the user into a particular cluster and recommend the user the movies that he/she may like based on the feedback given by users who fall in the same cluster. MOVIEREC application aims at reducing the time spent in searching for a movie of his/her taste and thereby increasing chances of getting value for their movies.
Keywords:Collaborative Filtering , Content-based Recommender system , Expert Users ,Cluster Formation ,K-Means