Multi-objective recommender systems (MORS) provide suggestions to users according to multiple (and possibly conflicting) goals. When a system optimizes its results at the individual-user level, it tailors them on a user's propensity towards the different objectives. Hence, the capability to understand users' fine-grained needs towards each goal is crucial. In this paper, we present the results of a user study in which we monitored the way users interacted with recommended items, as well as their self-proclaimed propensities towards relevance, novelty and diversity objectives. The study was divided into several sessions, where users evaluated recommendation lists originating from a relevance-only single-objective baseline as well as MORS. We show that despite MORS-based recommendations attracted less selections, its presence in the early sessions is crucial for users' satisfaction in the later stages. Surprisingly, the self-proclaimed willingness of users to interact with novel and diverse items is not always reflected in the recommendations they accept. Post-study questionnaires provide insights on how to deal with this matter, suggesting that MORS-based results should be accompanied by elements that allow users to understand the recommendations, so as to facilitate their acceptance.

翻译：多目标推荐系统根据多个（可能相互冲突的）目标向用户提供建议。当系统在个体用户层面优化其结果时，它会根据用户对不同目标的倾向来定制推荐。因此，理解用户对每个目标的细粒度需求至关重要。本文展示了一项用户研究的结果，我们监测了用户与推荐物品的交互方式，以及他们自述对相关性、新颖性和多样性目标的倾向。该研究分为多个会话，用户评估了源自仅基于相关性的单目标基线以及多目标推荐的推荐列表。我们表明，尽管基于多目标推荐的推荐吸引的选择较少，但其在早期会话中的出现对用户后期的满意度至关重要。令人惊讶的是，用户自述的与新颖和多样性物品交互的意愿并不总能反映在他们接受的推荐中。研究后问卷提供了如何处理此问题的见解，表明基于多目标推荐的结果应附带允许用户理解推荐的元素，以促进其接受。