Silvia Uribe

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—Content personalization provides a clear economical advantage over traditional content delivery since it contributes to increase the value of a given media service. This paper describes a new intelligent system for content flow personalization over mobile television environments.
Content personalization is a key element in the media content environment since it contributes to improve the user's experience. In this paper we present a novel intelligent content personalization system for content flow personalization over mobile broadcasting networks and terminals based on user profiling and clustering taking advantage of the(More)
One of the advantages of social networks is the possibility to socialize and personalize the content created or shared by the users. In mobile social networks, where the devices have limited capabilities in terms of screen size and computing power, Multimedia Recommender Systems help to present the most relevant content to the users, depending on their(More)
Many businesses have advertisement as their primary source of revenue. Print and Audio Visual media are on forefront in this area. In today's technology obsessed world, advertisement also forms a major source of revenue for service providers, app developers who work on mobile platforms. Advertisement on mobile platforms differs a lot from traditional(More)
Content personalisation is one of the main aims of the mobile media delivery business models, as a new way to improve the user's experience. In broadcasting networks, the content is sent "one to many", so a complete personalisation where the user may select any content is not possible. But using the mobile bidirec-tional return channel (e.g. UMTS(More)
The personalization and adaptation of user interfaces for multimedia search engines is a subject widely studied to enhance the management of multimedia content search. In this paper, we present a new multimedia semantic search engine called BUSCAMEDIA and its adaptive user interface, which allows accessing the search system regardless of the content or user(More)
This paper describes a novel content-based image recommendation system based on new image low level descriptors derived from the well known MPEG-7 parameters. Furthermore, it also proposes the integration of this recommendation system into a content-aware network architecture to enhance and enrich the content delivery and improve user's experience.
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