GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Introduction: personalized views of personalization
Communications of the ACM
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Decision Rules, Bayes' Rule and Ruogh Sets
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
TV Program Recommendation for Multiple Viewers Based on user Profile Merging
User Modeling and User-Adapted Interaction
An emergent role for TV in social communication
Proceedings of the seventh european conference on European interactive television conference
Semantic ambient media--an introduction
Multimedia Tools and Applications
Connecting the real world with the ubiquitous overlay in ambient media
EiMM '09 Proceedings of the 1st ACM international workshop on Events in multimedia
Qualitative analysis of user-based and item-based prediction algorithms for recommendation agents
Engineering Applications of Artificial Intelligence
Modeling and Coordinating Social Interactions in Pervasive Environments
ICECCS '11 Proceedings of the 2011 16th IEEE International Conference on Engineering of Complex Computer Systems
A context-aware music recommendation system using fuzzy bayesian networks with utility theory
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Incremental collaborative filtering for highly-scalable recommendation algorithms
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
TV3P: an adaptive assistant for personalized TV
IEEE Transactions on Consumer Electronics
Design and implementation of a universal appliance controller based on selective interaction modes
IEEE Transactions on Consumer Electronics
Socially aware tv program recommender for multiple viewers
IEEE Transactions on Consumer Electronics
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In this paper the authors are proposing a design of TV program and settings recommendation engine utilizing contextual parameters like personal, social, temporal, mood, and activity. In addition to the contextual parameters the system utilizes the explicit or implicit user ratings and watching history to resolve the conflict if any while recommending the services. The System is implemented exploiting AI techniques like fuzzy logic and Rough Sets Based Decision Rules. The motivation behind the proposed work is i) to improve the user's satisfaction level and ii) to improve the social relationship between user and TV. The context aware recommender utilizes social context data as an additional input to the recommendation task alongside information of users and TV programs. They have analyzed the recommendation process and performed a subjective test to show the usefulness of the proposed system for small families.