The generalized arrival of Digital TV will lead to a significant increase in the amount of channels and programs available to end users, making it difficult to find interesting programs among a myriad of irrelevant contents. Thus, in this field, automatic content recommenders should receive special attention in the following years to improve assistance to users. Current approaches of content recommenders have significant well-known deficiencies that hamper their wide acceptance. In this paper, a new approach for automatic content recommendation is presented that considerably reduces those deficiencies. This approach, based on the so-called Semantic Web technologies, has been implemented in the AVATAR tool, a hybrid content recommender that makes extensive use of well-known standards, such as TV-Anytime and OWL. Our proposal has been evaluated experimentally with real users, showing significant increases in the recommendation accuracy with respect to other existing approaches.

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IDTV experts broadly agree that in order to prevent the learner from abandoning t-learning experiences, it is necessary to take into account his/her particular preferences by means of a personalized experience. In this paper we introduce our personalized t-learning architecture: t-MAESTRO 1 .

Nowadays, we are living in a time of important technological changes that affect our lives at home and our communication with the outside world. Among them, the developments in Interactive Digital TV (IDTV) and the smart home field can be considered as particularly important. Related to the former, the new Set‐Top Boxes (STBs) are not only a decoder for digital television broadcast but also an entry point to the Information Society and a suitable platform to support the execution of interactive applications. With regards to the latter, the Residential Gateways (RGs) combine different network technologies to allow the connection of different electronics devices and appliances at home, not only with each other but also with the Internet. Since there is no widespread consensus about the configurations and functions of the RGs, we propose to coordinate the two aforementioned worlds by extending the functionality of STBs to become a RG. Our proposal consists of merging the Multimedia Home Platform (MHP), one of the main standard frameworks for IDTV, with Open Service Gateway Initiative (OSGi), the most widely used open platform to set up RGs. To overcome the radically different nature of these specifications—the function‐oriented MHP middleware and the service‐oriented OSGi framework—we define a new kind of application, coined as XbundLET. This application is able to bridge the gap between the two frameworks and make their interaction feasible. We also show how this proposal has the potential to enable the production of scenarios that cannot currently be put into practice in a natural way. Copyright © 2006 John Wiley & Sons, Ltd.