TY - GEN
T1 - Strategy-specific preference elicitation for group recommender
AU - Ziaras, Stefan Dimitri
AU - Wörndl, Wolfgang
N1 - Publisher Copyright:
© 2019 Copyright is held by the owner/author(s). Publication rights licensed to ACM
PY - 2019/9/8
Y1 - 2019/9/8
N2 - Group recommender systems propose items to a group of users by taking the preferences of individuals into account. Preference elicitation interfaces in existing solutions mostly use 5-point rating scales and are not tailored for group tasks and the underlying aggregation strategies. There is little work that addresses the design of suitable preference elicitation interfaces for group scenarios. In this paper, we propose, prototype, and evaluate novel user interface concepts that are tailored for aggregation strategies. In total, we introduce 8 solutions which seek to make the underlying strategies more transparent to the users. We present two user interfaces for each selected strategy and compare them in a user study. The results demonstrate that the presented prototypes were well received by most of the participants. Except for one draft solution, most participants agreed or strongly agreed that the proposed user interfaces are suitable for the respective strategy. Moreover, our findings suggest that there is a correlation between the complexity of aggregation strategies and the feedback received by the participants. This implies that it makes sense to hide the underlying logic when using complicated strategies. Furthermore, the results indicate that user interface elements should be tailored to the aggregation strategy.
AB - Group recommender systems propose items to a group of users by taking the preferences of individuals into account. Preference elicitation interfaces in existing solutions mostly use 5-point rating scales and are not tailored for group tasks and the underlying aggregation strategies. There is little work that addresses the design of suitable preference elicitation interfaces for group scenarios. In this paper, we propose, prototype, and evaluate novel user interface concepts that are tailored for aggregation strategies. In total, we introduce 8 solutions which seek to make the underlying strategies more transparent to the users. We present two user interfaces for each selected strategy and compare them in a user study. The results demonstrate that the presented prototypes were well received by most of the participants. Except for one draft solution, most participants agreed or strongly agreed that the proposed user interfaces are suitable for the respective strategy. Moreover, our findings suggest that there is a correlation between the complexity of aggregation strategies and the feedback received by the participants. This implies that it makes sense to hide the underlying logic when using complicated strategies. Furthermore, the results indicate that user interface elements should be tailored to the aggregation strategy.
KW - Group recommender systems
KW - Social choice
KW - User interfaces
KW - User study
UR - http://www.scopus.com/inward/record.url?scp=85072793814&partnerID=8YFLogxK
U2 - 10.1145/3340764.3344452
DO - 10.1145/3340764.3344452
M3 - Conference contribution
AN - SCOPUS:85072793814
T3 - ACM International Conference Proceeding Series
SP - 531
EP - 535
BT - Mensch und Computer 2019, MuC 2019 - Tagungsband
A2 - Alt, Florian
A2 - Bulling, Andreas
A2 - Doring, Tanja
PB - Association for Computing Machinery
T2 - 2019 Conference on Mensch und Computer, MuC 2019
Y2 - 8 September 2019 through 11 September 2019
ER -