以用户为中心的评价策略,为群体推荐兴趣点序列

Daniel Herzog, W. Wörndl
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引用次数: 11

摘要

大多数推荐系统(RSs)预测个人用户的偏好;然而,在某些情况下,需要为一组用户提出建议。旅游业是团体推荐的热门领域,因为人们经常组团旅行,并在旅行中寻找兴趣点(POI)序列。在这项研究中,我们提出了不同的策略,可用于推荐POI序列的群体。此外,我们还引入了一些新颖的方法,包括一种叫做“分组”的策略,它允许团队在旅行中分成更小的团队。我们将用户研究中的所有策略与40个真实群体进行了比较。我们的结果证明,使用不同策略生成的推荐质量有显著差异。大多数团体都愿意在旅行中暂时分开,即使他们和身边的人一起旅行。在本例中,Split Group针对不同的评估标准生成了最佳建议。我们利用这些发现对旅游领域的团体推荐策略提出改进建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
User-centered evaluation of strategies for recommending sequences of points of interest to groups
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.
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