TY - GEN
T1 - A user study on groups interacting with tourist trip recommender systems in public spaces
AU - Herzog, Daniel
AU - Wörndl, Wolfgang
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/6/7
Y1 - 2019/6/7
N2 - Tourist groups exploring a city often face the problem of finding a sequence of points of interest that satisfies all group members. In this work, we present three different configurations of a group recommender system that suggests such trips even when tourists are already traveling: connecting multiple smartphones, sharing a public display, and combining both devices in a distributed user interface approach. We conducted a large user study with real groups to evaluate these configurations. Our results show that public displays are attractive for users who prefer an open discussion of their preferences. However, we have empirical evidence that decisions on group preferences often tend to be unfair for some group members, especially when they do not know each other very well. A distributed recommender system aggregating group members' individual preferences fairly with the option to display selected content on a public display was the most appreciated solution for overcoming this problem.
AB - Tourist groups exploring a city often face the problem of finding a sequence of points of interest that satisfies all group members. In this work, we present three different configurations of a group recommender system that suggests such trips even when tourists are already traveling: connecting multiple smartphones, sharing a public display, and combining both devices in a distributed user interface approach. We conducted a large user study with real groups to evaluate these configurations. Our results show that public displays are attractive for users who prefer an open discussion of their preferences. However, we have empirical evidence that decisions on group preferences often tend to be unfair for some group members, especially when they do not know each other very well. A distributed recommender system aggregating group members' individual preferences fairly with the option to display selected content on a public display was the most appreciated solution for overcoming this problem.
KW - Fairness
KW - Group decision
KW - Group recommender system
KW - Tourist trip recommendation
KW - User interface
KW - User study
UR - http://www.scopus.com/inward/record.url?scp=85068073308&partnerID=8YFLogxK
U2 - 10.1145/3320435.3320449
DO - 10.1145/3320435.3320449
M3 - Conference contribution
AN - SCOPUS:85068073308
T3 - ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization
SP - 130
EP - 138
BT - ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization
PB - Association for Computing Machinery, Inc
T2 - 27th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2019
Y2 - 9 June 2019 through 12 June 2019
ER -