Recommender System Framework Using Clustering and Collaborative Filtering
Namita Mittal, Richi Nayak, Mahesh Chandra Govil, Karishma Jain · 2010
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.