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Diversity in Recommender Systems: Bridging the gap between users and systems

Authors:
Laurent Candillier
Max Chevalier
Damien Dudognon
Josiane Mothe

Keywords: Information Retrieval; Recommender System; Document similarity; Diversity

Abstract:
Recommender systems aim at automatically providing objects related to user’s interests. The angular stone of such systems is a way to identify documents to be recommended. Indeed, the quality of these systems depends on the accuracy of its recommendation selection method. Thus, the selection method should be carefully chosen in order to improve end-user satisfaction. In this paper, we first compare two sets of approaches from the literature to underline that their results are significantly different. We also provide the conclusion of a survey done by thirty four students showing that diversity is considered as important in recommendation lists. Finally, we show that combining existing recommendation selection methods is a good mean to obtain diversity in recommendation lists.

Pages: 48 to 53

Copyright: Copyright (c) IARIA, 2011

Publication date: October 23, 2011

Published in: conference

ISSN: 2308-3492

ISBN: 978-1-61208-167-0

Location: Barcelona, Spain

Dates: from October 23, 2011 to October 29, 2011