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The wide development of mobile applications provides a considerable amount of data of all types (images, texts, sounds, videos, etc.). In this sense, Mobile Context-aware Recommender Systems (MCRS) suggest the user suitable information depending on her/his situation and interests. Two key questions have to be considered 1) how to recommend the user information that follows his/her interests evolution?...
In existing mobile content service systems, the study is quite rare on automatic situation-service rule construction. Hence, a method is proposed that the semantic association rules between situations and preferences are built by quantitative frequent marked lattice. Different recommendation rules can be extracted along multi-dimensional context routes from this lattice structure. It is propitious...
Context-aware adaptive systems aim at automatically personalizing the user's environment depending on the user's situation, and hence, minimizing user interaction with the system. We present a novel user profile ontology that is dedicated to describe situation-dependent sub-profiles. This ontology can be used by context-aware adaptive service platforms for mobile communication and information services...
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