Abstract
This paper compares five different ways of interacting with an
attribute-based recommender system and shows that different
types of users prefer different interaction methods. In an online
experiment with an energy-saving recommender system the interaction
methods are compared in terms of perceived control, understandability,
trust in the system, user interface satisfaction, system
effectiveness and choice satisfaction. The comparison takes into
account several user characteristics, namely domain knowledge,
trusting propensity and persistence. The results show that most
users (and particularly domain experts) are most satisfied with a
hybrid recommender that combines implicit and explicit preference
elicitation, but that novices and maximizers seem to benefit
more from a non-personalized recommender that just displays the
most popular items.
Original language | English |
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Title of host publication | RecSys '11 Proceedings of the fifth ACM International Conference on Recommender Systems, 23-27 October 2011, Chicago, Il., USA |
Editors | B. Mobasher, R. Burke |
Place of Publication | New York |
Publisher | Association for Computing Machinery, Inc |
Pages | 141-148 |
ISBN (Print) | 978-1-4503-0689-6 |
DOIs | |
Publication status | Published - 2011 |
Event | 5th ACM Conference on Recommender Systems (RecSys 2011) - Chicago, United States Duration: 23 Oct 2011 → 27 Oct 2011 Conference number: 5 https://recsys.acm.org/recsys11 |
Conference
Conference | 5th ACM Conference on Recommender Systems (RecSys 2011) |
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Abbreviated title | RecSys 2011 |
Country/Territory | United States |
City | Chicago |
Period | 23/10/11 → 27/10/11 |
Internet address |