Recommender System Framework Using Clustering and Collaborative Filtering

Collaborative filtering is becoming greatly popular as it contributes in reducing information overload. Collaborative filtering based recommender system focuses on predicting new items of interest for a user based on correlations computed between that user and other users. In this paper we propose a framework based on, application of data partitioning/clustering algorithm on ratings dataset followed by collaborative filtering for developing a Movie Recommender System. The proposed system reduces the computation time considerably and increases the prediction accuracy.