Recommender: Helping viewers in their choice for educational programs in digital TV context

Currently in Brazil, a fundamental change is taking place in TV: the migration from analogue to digital TV system. This change has two main implications: an increase in transmission capacity for new channels with the same bandwidth and the ability to send applications with multiplexed audio-visual content. Brazilian government aims to exploit the transmission capacity for new channels offering programming created to distance learning and thereby promoting social inclusion in the vast majority of the population. This information overload demands mechanisms to help students to browse and select what education programs are best suited to their current level. Personalized recommendation systems emerge as a solution to this problem, providing the viewer with educational programs relevant to his profile. In this paper we present a personalized recommendation system, the Recommender consistent with the reference implementation of the Brazilian digital TV system. Finally, we present the results obtained after using the proposed system.