scispace - formally typeset
Y

Yolanda Blanco-Fernández

Researcher at University of Vigo

Publications -  129
Citations -  1367

Yolanda Blanco-Fernández is an academic researcher from University of Vigo. The author has contributed to research in topics: Recommender system & Personalization. The author has an hindex of 18, co-authored 128 publications receiving 1303 citations.

Papers
More filters
Journal ArticleDOI

User-generated contents and reasoning-based personalization

TL;DR: A mobile TV system that broadcasts user-generated audiovisual contents for handheld devices in a mobile network based on the DVB-H broadcasting standard that adopts well-known technologies for broadcasting and semantic annotation of audiovISual contents, as well as emergent technology from the so-called Web 2.0.
Proceedings ArticleDOI

A technological framework for TV-supported collaborative learning

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.
Journal IssueDOI

An MHP framework to provide intelligent personalized recommendations about digital TV contents

TL;DR: A new approach for automatic content recommendation is presented, based on Semantic Web technologies, that significantly reduces deficiencies in the current content recommenders and performs better than other existing approaches.
Journal ArticleDOI

Methodologies to evolve formal specifications through refinement and retrenchment in an analysis–revision cycle

TL;DR: This article introduces methodologies to conduct an interactive and integrated approach, grounded on the formalization of two basic types of evolutions (refinements and retrenchments) over multi-valued specification and modeling formalisms.
Journal ArticleDOI

A semantic approach to avoiding fake neighborhhoods in collaborative recommmendation of coupons through Digital TV

TL;DR: This paper applies semantic reasoning techniques to avoid fake neighborhoods in collaborative filtering strategies and proposes matching the recommended coupons to TV contents semantically related with them, in order to increase their redemption.