Poi Enhanced Video Recommender System Using Collaboration and Social Networks

Abstract

Every day, the number of videos available in the world increases. For instance, there is a vast amount of video websites, like Youtube and NetFlix, VOD services, as well as PVR devices that automatically record videos, 24 hours a day. Apparently this situation allows a large possibility of choice for the user, on the other hand, it creates an overload problem, i.e., a difficulty to find the correct content for the user needs. One of the ways to treat such an overload is the use of recommender systems, which filter the content in order to deliver what is most interesting to the user. This paper presents an approach that allows the annotation of points of interest on videos on the Web. Through this, users can mark their most interesting points on the videos. This information can thus be used in conjunction with the user profile and interests to provide recommendations. The differential of this paper is to show how points of interest can be used to enhance video recommender systems and how to design social networks of users with common interest points. 2 RELATED WORKS There are many works about video recommender 717