Video recommendation using neuro-fuzzy on social TV environment

Abstract

Prior collaborative filtering (CF) methods based on neighbors’ ratings to predict a target user’s rating. In this work, we consider recommendation on the context of Social TV (STV). The watchers/users may either share, comment, rate, or tag videos they are interested in. Each video must be watched and rated by many users. For these assumptions, we proposed a novel model-based collaborative filtering using a fuzzy neural network to learn user’s social web behaviors for video recommendation on STV. We use netflix data-set to evaluate the proposed method. The result shown that the proposed approach is a significant effective method.