Context-Aware Media Recommendations

Abstract

Media content recommendations for a mobile user based on his changing contextual preferences, otherwise called context-aware media recommendations, constitute a very important challenge. Context-aware media recommendation systems take context information such as user preferences, activities, time, location, device, and network capabilities as inputs for media recommendations, whereas the traditional recommendation systems use only user preferences in the form of ratings to deliver media recommendations. This paper presents a generic high-level architecture of context-aware recommendations, discussing its key techniques and solutions, which are based on context acquisition, recognition, and representations, using MPEG-21 and ontology model, and a contextual user profiling process, as well as MPEG-7 for media description model and media presentation adaptation.