System Rekomendacyjny Item-based Collaborative Filtering

Abstract

With the advance of technologies, there are numerous movies produced annually, which leads to information overload for the audience. Recommender was designed to overcome that issue and personalize the audience experience. This paper describes Item-based Collaborative Filtering Recommender, and reveals how the model predicts movie ratings on MovieLens data set. As shown at the end of this paper, the model outperforms the other movie recommender models.