Type

Journal Article

Authors

Alan F. Smeaton
Kieran McDonald
Barry Smyth
David C. Wilson
Dermot O'Sullivan

Subjects

Computer Science

Topics
digital video telecommunication personalization artificial intelligence digital tv collaborative filtering case based reasoning similarity maintenance data mining

Improving the quality of the personalized electronic program guide (2004)

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.
Collections Ireland -> Dublin City University -> Subject = Computer Science: Artificial intelligence
Ireland -> Dublin City University -> Publication Type = Article
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: Centre for Digital Video Processing (CDVP)
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Engineering: Telecommunication
Ireland -> Dublin City University -> Subject = Computer Science: Digital video
Ireland -> Dublin City University -> Subject = Engineering
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres

Full list of authors on original publication

Alan F. Smeaton, Kieran McDonald, Barry Smyth, David C. Wilson, Dermot O'Sullivan

Experts in our system

1
Alan F. Smeaton
Dublin City University
Total Publications: 475
 
2
Barry Smyth
University College Dublin
Total Publications: 147
 
3
Dermot O'Sullivan
Dublin City University