User Modeling and User-Adapted Interaction

, Volume 14, Issue 1, pp 5–36 | Cite as

Improving the Quality of the Personalized Electronic Program Guide

  • Derry O’Sullivan
  • Barry Smyth
  • David C. Wilson
  • Kieran McDonald
  • Alan Smeaton
Article

Abstract

As Digital TV subscribers are offered more and more channels, it is becoming increasingly difficult for them to locate the right programme information at the right time. The personalized Electronic Programme Guide (pEPG) is one solution to this problem; it leverages artificial intelligence and user profiling techniques to learn about the viewing preferences of individual users in order to compile personalized viewing guides that fit their individual preferences. Very often the limited availability of profiling information is a key limiting factor in such personalized recommender systems. For example, it is well known that collaborative filtering approaches suffer significantly from the sparsity problem, which exists because the expected item-overlap between profiles is usually very low. In this article we address the sparsity problem in the Digital TV domain. We propose the use of data mining techniques as a way of supplementing meagre ratings-based profile knowledge with additional item-similarity knowledge that can be automatically discovered by mining user profiles. We argue that this new similarity knowledge can significantly enhance the performance of a recommender system in even the sparsest of profile spaces. Moreover, we provide an extensive evaluation of our approach using two large-scale, state-of-the-art online systems—PTVPlus, a personalized TV listings portal and Físchlár, an online digital video library system.

case-based reasoning collaborative filtering data mining digital TV personalization similarity maintenance 

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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Derry O’Sullivan
    • 1
  • Barry Smyth
    • 1
  • David C. Wilson
    • 1
  • Kieran McDonald
    • 2
  • Alan Smeaton
    • 2
  1. 1.Smart Media InstituteUniversity College DublinDublin 4Ireland
  2. 2.Centre for Digital Video ProcessingDublin City UniversityDublin 9Ireland

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