Exploring New Ways for Personalized E-Commerce through Digital TV

  • Yolanda Blanco-Fernández
  • Martín López-Nores
  • José J. Pazos-Arias
  • Manuela I. Martín-Vicente
Part of the Studies in Computational Intelligence book series (SCI, volume 418)


The evolution of information technologies is consolidating recommender systems as essential tools in e-commerce.To date, these systems have focused on discovering the items that best match the preferences, interests and needs of individual users, to end up listing those items by decreasing relevance in some menus. In this paper,we propose extending the current scope of recommender systems to better support trading activities, by automatically generating interactive applications that provide the users with personalized commercial functionalities related to the selected items. We explore this idea in the context of Digital TV advertising, with a system that provide personalized commercial functionalities, gathering contents from multiple sources and bring together semantic reasoning techniques, SWRL rules and new architectural solutions for web services and mashups.


Recommender System Semantic Similarity Domain Ontology Semantic Concept Lower Common Ancestor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yolanda Blanco-Fernández
    • 1
  • Martín López-Nores
    • 1
  • José J. Pazos-Arias
    • 1
  • Manuela I. Martín-Vicente
    • 1
  1. 1.Department of Telematics EngineeringUniversity of Vigo, EE TelecomunicaciónVigoSpain

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