User-Centered Evaluation of Strategies for Recommending Sequences of Points of Interest to Groups

被引:10
作者
Herzog, Daniel [1 ]
Woerndl, Wolfgang [1 ]
机构
[1] Tech Univ Munich, Dept Informat, D-85748 Garching, Germany
来源
RECSYS 2019: 13TH ACM CONFERENCE ON RECOMMENDER SYSTEMS | 2019年
关键词
Recommender System; Group Recommendation; Sequence; Preference Aggregation; Social Choice Strategy; User Study;
D O I
10.1145/3298689.3346988
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Most recommender systems (RSs) predict the preferences of individual users; however, in certain scenarios, recommendations need to be made for a group of users. Tourism is a popular domain for group recommendations because people often travel in groups and look for point of interest (POI) sequences for their visits during a trip. In this study, we present different strategies that can be used to recommend POI sequences for groups. In addition, we introduce novel approaches, including a strategy called Split Group, which allows groups to split into smaller groups during a trip. We compared all strategies in a user study with 40 real groups. Our results proved that there was a significant difference in the quality of recommendations generated by using the different strategies. Most groups were willing to split temporarily during a trip, even when they were traveling with persons close to them. In this case, Split Group generated the best recommendations for different evaluation criteria. We use these findings to propose improvements for group recommendation strategies in the tourism domain.
引用
收藏
页码:96 / 100
页数:5
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