Ana Fernández Vilas

Recommender systems arose with the goal of helping users search in overloaded information domains (like e-commerce, e-learning or Digital TV). These tools automatically select items (commercial products, educational courses, TV programs, etc.) that may be appealing to each user taking into account his/her personal preferences. The personalization strategies used to compare these preferences with the available items suffer from well-known deficiencies that reduce the quality of the recommendations. Most of the limitations arise from using syntactic matching techniques because they miss a lot of useful knowledge during the recommendation process. In this paper, we propose a personalization strategy that overcomes these drawbacks by applying inference techniques borrowed from the Semantic Web. Our approach reasons about the semantics of items and user preferences to discover complex associations between them. These semantic associations provide additional knowledge about the user preferences, and permit the recommender system to compare them with the available items in a more effective way. The proposed strategy is flexible enough to be applied in many recommender systems, regardless of their application domain. Here, we illustrate its use in AVATAR, a tool that selects appealing audiovisual programs from among the myriad available in Digital TV.

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.

Page 1. Reusing Verification Information of Incomplete Specifications Rebeca P. Díaz Redondo, José J. Pazos Arias and Ana Fernández Vilas Departamento de Enxeñería Telemática. University of Vigo. 36200 Vigo. Spain {rebeca, jose, avilas}@det.uvigo.es Abstract ...

Current recommender systems attempt to identify appealing items for a user by applying syntactic matching techniques, which suffer from significant limitations that reduce the quality of the offered suggestions. To overcome this drawback, we have developed a domain-independent personalization strategy that borrows reasoning techniques from the Semantic Web, elaborating recommendations based on the semantic relationships inferred between the user’s preferences and the available items. Our reasoning-based approach improves the quality of the suggestions offered by the current personalization approaches, and greatly reduces their most severe limitations. To validate these claims, we have carried out a case study in the Digital TV field, in which our strategy selects TV programs interesting for the viewers from among the myriad of contents available in the digital streams. Our experimental evaluation compares the traditional approaches with our proposal in terms of both the number of TV programs suggested, and the users’ perception of the recommendations. Finally, we discuss concerns related to computational feasibility and scalability of our approach.

Internet is open 24 hours a day, 7 days a week, so hardware, software, and communications must be always online. Additionally, the total number of users and its workload is completely unpredictable. If you decide to use web services, you will have no solution for problems like those. This paper shows a new technique that can be applied to web services technology in order to be able to deploy web services with high availability features using clustering. This new technique is based on the virtualization of the real web services used to serve the client requests, creating new virtual web services that will be the ones invoked by the clients. At the back-end, the implementation web services (the real ones) will be invoked inside a cluster.

We propose a schema to support the composition of OSGi services as result of orchestrating atomic services at runtime. So, the composite functionality is published in the OSGi service registry, although there is no bundle implementing it, i.e. it is a virtual service. With this proposal the OSGi potentiality increases because of the huge amount of new services that can be offered as a result of appropriate combinations.

In an increasingly competitive market, stakeholders of the television industry strive to exploit all the possibilities to get revenues from advertising, but their practices are usually at odds with the comfort of the TV viewers. This paper presents the proof of concept of MiSPOT, a system that brings a non-invasive and fully personalized form of advertising to Interactive Digital TV, targeting both domestic and mobile receivers. MiSPOT employs semantic reasoning techniques to select advertisements suited to the preferences, interests and needs of each individual viewer, and then relies on multimedia composition abilities to blend the advertising material with the TV program he/she is viewing at any time. The advertisements can be set to launch interactive commercials, thus enabling means for the provision of t-commerce services. Evaluation experiments are described to show the technical viability of the proposal, and also to gauge the opinions of end users. Questions about the potential impact and exploitation of this new form of advertising are addressed too.

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.

Multimed Tools Appl (2009) 41:407–436 DOI 10.1007/s11042-008-0239-7 ... Receiver-side semantic reasoning for digital TV personalization in the absence of return channels ... Martín López-Nores·Yolanda Blanco-Fernández·José J. Pazos-Arias· Jorge ...

Abstract: 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 ...

Interactive Digital TV (IDTV) opens new learning possibilities where new forms of education are needed. In this paper we explain a new conception of t-learning experiences where TV programs and learning contents are combined. In order for its creation to be possible we will use Adaptive Hypermedia techniques and Semantic Reasoning to design an Intelligent Tutoring System (ITS) whose tasks consist in selecting, combining and personalizing the contents to construct these learning experiences.

The development of requirements specifications has to face the incomplete and often inac-curate knowledge available about the desired systems at the early stages of development. As a result, it is rather frequent that developers claim to have described exactly what they ...