In this paper we study the synergy between user behavior, context data, and semantic information in order to enable future services to adapt to different situations based on the recommendations of a service-independent recommender. Therefore, we propose a system that delivers context-aware recommendations, which are based on provided feedback, context data, and an ontology-based content categorization scheme. We provide a detailed overview of the specification, a short description of a possible service scenario and a discussion of the results.
