A Collaborative Filtering based Approach to Classify Movie Genres using User Ratings

Abstract

In this paper, we present an approach for classifying movie genres based on user-ratings. Our approach is based on collaborative filtering (CF), a common technique used in recommendation systems, where the similarity between movies based on user-ratings, is used to predict the genres of movies. The results of conducted experiments show that our genres classification approach outperforms many existing approaches, by achieving an F1-score of 0.70, and a hit-rate of 94\%. We also construct a multilayer network of movies, with genres as layers. We apply agglomerative clustering on the layers of this network to obtain a comprehensible taxonomy of genres which groups together similar genres using the similarity of their movies in terms of user preferences.