Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
Personalized Content Retrieval in Context Using Ontological Knowledge
IEEE Transactions on Circuits and Systems for Video Technology
Music recommendations with temporal context awareness
Proceedings of the fourth ACM conference on Recommender systems
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We describe here a system oriented towards personalized selection and delivery of heterogeneous multimedia content. It is designed to go along with the user during the whole day seamlessly and provide on demand delivery of relevant multi-modal content, stemming from diverse sources. A set of specially designed recommendation engines provides personalization adapted to the instantaneous context of the user. We describe the overall architecture and usability principles of the system, and subsequently we focus in detail on some of its subsystems.