Recommendations with personalized explanations have been shown to increase user trust and perceived quality and help users make better decisions. Moreover, such explanations allow users to provide feedback by critiquing them. Several algorithms for recommender systems with multi-step critiquing have therefore been developed. However, providing a user-friendly interface based on personalized explanations and critiquing has not been addressed in the last decade. In this paper, we introduce four different web interfaces (available under https://lia.epfl.ch/critiquing/) helping users making decisions and finding their ideal item. We have chosen the hotel recommendation domain as a use case even though our approach is trivially adaptable for other domains. Moreover, our system is model-agnostic (for both recommender systems and critiquing models) allowing a great flexibility and further extensions. Our interfaces are above all a useful tool to help research in recommendation with critiquing. They allow to test such systems on a real use case and also to highlight some limitations of these approaches to find solutions to overcome them.
翻译:个人化解释的建议已经表明可以提高用户信任度和感知质量,帮助用户做出更好的决定。此外,这种解释还允许用户通过验证来提供反馈。因此,已经为具有多步爬动性的建议系统制定了几种算法。然而,过去十年没有讨论过基于个性化解释和滑动性的用户友好界面。在本文中,我们引入了四个不同的网络界面(见https://lia.epfl.ch/critiquining/),帮助用户作出决定和找到理想项目。我们选择了旅馆建议域作为使用案例,尽管我们的方法对其他领域适应性极差。此外,我们的系统是模型-不可知性(对于推荐系统和滑动模型),允许很大的灵活性和进一步的扩展。我们的界面首先是一种有用的工具,有助于在建议中研究关于滑动性的建议。它们允许在实际使用的情况下测试这些系统,并突出这些方法在寻找克服这些系统的方法上的一些局限性。