Yolanda Blanco-Fernández

TL;DR: A filtering strategy that exploits the semantics formalized in an ontology in order to link items (and their features) to time functions and reveals significant improvements of recommendation precision with regard to previous time-driven filtering approaches.

TL;DR: 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 is introduced.

TL;DR: This work introduces a filtering strategy centered on the properties that characterize the items and the users, which in turn serves to present the recommendations in a much more enticing manner.

TL;DR: A new strategy is proposed based on semantic reasoning that aims to improve the neighborhood formation in order to overcome the aforementioned fake neighborhood problem and is aimed at making more flexible the search for semantic similarities between different products, and thus not require users to rate the same products inorder to be compared.

TL;DR: MiSPOT is presented, a system that brings a non-invasive and fully personalized form of advertising to Interactive Digital TV, targeting both domestic and mobile receivers, and employs semantic reasoning techniques to select advertisements suited to the preferences, interests and needs of each individual viewer.