Showing papers by "Manuel Ramos-Cabrer published in 2004"
22 Nov 2004
TL;DR: In this paper, a recommender system of personalized TV contents, named AVATAR, is presented, whose main novelty is the semantic reasoning about user preferences and historical logs, to improve the traditional syntactic content search.
Abstract: In this paper a recommender system of personalized TV contents, named AVATAR, is presented. We propose a modular multi-agent architecture for the system, whose main novelty is the semantic reasoning about user preferences and historical logs, to improve the traditional syntactic content search. Our approach uses Semantic Web technologies – more specifically an OWL ontology – and the TV-Anytime standard to describe the TV contents. To reason about the ontology, we have defined a query language, named LIKO, for inferring knowledge from properties contained in it. In addition, we show an example of a semantic recommendation by means of some LIKO operators.
31 citations
13 Dec 2004
TL;DR: This paper presents a recommender system of personalized TV contents, called AVATAR, for which a modular multiagent architecture is proposed, that combines different knowledge inference strategies (such as Bayesian techniques, profiles matching and semantic reasoning), and focuses on the description of one of these strategies, the naive Bayesian classifiers.
Abstract: In this paper we present a recommender system of personalized TV contents, called AVATAR, for which we propose a modular multiagent architecture, that combines different knowledge inference strategies (such as Bayesian techniques, profiles matching and semantic reasoning) We focus on the description of one of these strategies, the naive Bayesian classifiers, explaining an example in the context of personalized digital television In order to represent the knowledge in the television domain, we have developed TV contents ontology, to infer new data from the known information Besides, the TV-anytime specification has been used referred to the description of contents and the management of user preferences and their activity logs The proposed recommender system has been conceived as an application conforming to multimedia home platform (MHP) standard, to be distributed over the broadcast transport stream that is tuned by the user receiver
23 citations
13 Dec 2004
TL;DR: A technological framework for the development and deployment of distributed and collaborative educational services for IDTV is introduced, proposing an extension to the multimedia home platform standard, based on a selection of freely available technologies that integrate into a CASE tool that bridges the gap between course-authoring and programming tasks.
Abstract: Interactive digital TV is emerging as a potentially important medium to create opportunities for learning at home. To date, the offer has been mostly based on the contents available through broadcast, but this is expected to change in the near future. The increasing availability of high-quality bidirectional networks, together with the fact that IDTV users are abandoning their passive habits, envisages a new range of highly interactive services that may enhance greatly the prospects of distance education. This paper introduces a technological framework for the development and deployment of distributed and collaborative educational services for IDTV, proposing an extension to the multimedia home platform standard. The framework is based on a selection of freely available technologies, which we integrate into a CASE tool that bridges the gap between course-authoring and programming tasks. We also discuss the possible market implications of our approach, because the ideas presented here contribute to openness in the field of IDTV services, so far monopolised by mainstream broadcasters.
14 citations
08 Aug 2004
TL;DR: An extension to the Multimedia Home Platform standard is proposed, aimed at providing better support for collaborative learning services and an architecture for such services is described and a selection of freely available technologies for their implementation are described.
Abstract: T-learning – the provision of educational services over Interactive Digital TV – is regarded as a complement to e-learning solutions, whose scope is limited due to the digital divide. The increasing connectivity, together with the fact that IDTV users are no longer passive spectators, permits to start thinking on highly interactive services that support fluid communication among users and service providers. This may enhance the prospects of learning at home, as long as the current offer is mostly based on broadcast content, with scarce use of return channels for feedback. This paper proposes an extension to the Multimedia Home Platform standard, aimed at providing better support for collaborative learning services. We describe an architecture for such services and a selection of freely available technologies for their implementation. We also discuss the possible market implications of our approach, as the ideas presented here contribute to openness in the field of IDTV services.
2 citations
Journal Article•
TL;DR: A modular multi-agent architecture for the system, whose main novelty is the semantic reasoning about user preferences and historical logs, is proposed to improve the traditional syntactic content search.
Abstract: In this paper a recommender system of personalized TV contents, named AVATAR 1 , is presented. We propose a modular multi-agent architecture for the system, whose main novelty is the semantic reasoning about user preferences and historical logs, to improve the traditional syntactic content search. Our approach uses Semantic Web technologies - more specifically an OWL ontology - and the TV-Anytime standard to describe the TV contents. To reason about the ontology, we have defined a query language, named LIKO, for inferring knowledge from properties contained in it. In addition, we show an example of a semantic recommendation by means of some LIKO operators.
2 citations