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When Diversity Is Needed... But Not expected!

Authors:
Sylvain Castagnos
Armelle Brun
Anne Boyer

Keywords: Recommender Systems, Diversity, User Modeling, User Study

Abstract:
Recent studies have highlighted the correlation between users' satisfaction and diversity within recommenders, especially the fact that diversity increases users' confidence when choosing an item. Understanding the reasons of this positive impact on recommenders is now becoming crucial. Based on this assumption, we designed a user study that focuses on the utility of this new dimension, as well as its perceived qualities. This study has been conducted on 250 users and it compared 5 recommendation approaches, based on collaborative filtering, content-based filtering and popularity, along with various degrees of diversity. Results show that, when recommendations are made explicit, diversity may reduce users' acceptance rate. However, it helps increasing users' satisfaction. Moreover, this study highlights the need to build users' preference models that are diverse enough, so as to generate good recommendations.

Pages: 44 to 50

Copyright: Copyright (c) IARIA, 2013

Publication date: November 17, 2013

Published in: conference

ISSN: 2326-9332

ISBN: 978-1-61208-311-7

Location: Lisbon, Portugal

Dates: from November 17, 2013 to November 21, 2013