Semantic TV Engine: An IPTV Enabler for Personalized Recommendations


With today's availability of an increasing amount of media content delivered by IPTV systems, the need for personalized content prepa- ration arises. In order to organize media content tailored to the users' needs, we are faced with challenges regarding data representation, integration and user profiling issues. Our approach is to use semantic technologies to build a unified data integration layer based on well- known ontologies and to apply a recommender system on top of the data plane that provides personalized recommendations considering the user's context. In this paper we introduce a high level overview of an enabler component for IPTV infrastructures, which combines semantic data management and recommendation functionalities. As a proof of concept we have developed an IPTV application that interacts with the new enabler.

Juri Glaß, Stefan Marx, Torsten Schmidt, Fikret Sivrikaya
Conference Paper
Int. Conf. on Language Resources and Evaluation (LREC 2010), 1st Workshop on Semantic Personalized Information Management (SPIM 2010)