Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Improving the Quality of the Personalized Electronic Program Guide
User Modeling and User-Adapted Interaction
Experiences with an Interactive Learning Environment in Digital TV
ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
A model for personalized learning through IDTV
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
An MHP framework to provide intelligent personalized recommendations about digital TV contents
Software—Practice & Experience
Receiver-side semantic reasoning for digital TV personalization in the absence of return channels
Multimedia Tools and Applications
MiSPOT: dynamic product placement for digital TV through MPEG-4 processing and semantic reasoning
Knowledge and Information Systems
Exploring synergies between digital tv recommender systems and electronic health records
Proceedings of the 8th international interactive conference on Interactive TV&Video
EducaTV: an architecture to access educational content through IDTV
WebMedia '09 Proceedings of the XV Brazilian Symposium on Multimedia and the Web
Investigating the added value of interactivity and serious gaming for educational TV
Computers & Education
Engineering Applications of Artificial Intelligence
Property-based collaborative filtering for health-aware recommender systems
Expert Systems with Applications: An International Journal
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E-learning technologies have developed greatly in recent years, with considerable success. However, there is increasing evidence that web-based learning is not reaching the social sectors which are more reluctant to contact with the new technologies, thus leading to inequalities in the access to education and knowledge in the Information Society. By hiding the intricacies of computers behind the familiarity of household equipment, Interactive Digital TV (IDTV) is considered to play a key role in addressing this problem, and the term t-learning has been recently coined to mean TV-based interactive learning. Despite several approaches to t-learning have been proposed, works are missing that conceive it as a whole, delimit its scope in comparison with web-based learning and analyze the influence of the normalization of IDTV as a services platform. This paper addresses these issues, and introduces a framework for the development and deployment of t-learning services that promotes interoperability and reuse while taking into account the characteristic features of the IDTV medium.