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Context relevance assessment and exploitation in mobile recommender systems

Baltrunas, Linas ; Ludwig, Bernd ; Peer, Stefan ; Ricci, Francesco


In order to generate relevant recommendations, a context-aware recommender system (CARS) not only makes use of user preferences, but also exploits information about the specific contextual situation in which the recommended item will be consumed. For instance, when recommending a holiday destination, a CARS could take into account whether the trip will happen in summer or winter. It is unclear, ...


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