Personalized electronic program guide for IPTV based on collaborative filtering with novel similarity method

We propose a personalized electronic program guide (EPG) for IPTV. It uses memory-based collaborative filtering with a fast and accurate similarity method. The user´s explicit interests-based proposed method predicts user´s ratings on unexperienced content not previously rated by the user, and then arranges the content in order of highest ratings and classifies them according to their attributes. We experimented on the prediction accuracy of the ratings in order to evaluate the proposed method. As a result, we confirmed that the proposed method is effective for high-speed rating prediction and has improved accuracy.