Customized IPTV content recommendation service model based on personal preference

Abstract

These days, the advent of the Age of Broadcasting and Telecommunication Convergence, the number of program contents available in IPTV services has rapidly increased. For that reason, the accessibility and selection to users' favorite broadcasting program contents has become an important issue. Moreover, due to the increase in the number of IPTV channels to a 3-digit number, it became difficult to select a channel only with the traditional TV viewing methods. In this paper, to solve this problem, an IPTV content recommendation service model which is used to user's favorite preferences is proposed. The proposed scheme tracks users' viewing and usage history to automatically monitor their preferences and recommends program contents suitable for them. User profiles data showing their preferences for programs allow users to be provided with more correct program recommendation services, by application of their previous viewing history, preferences of similar users and their favorite channels, to calculation of preferences.