Multi-Objective Recommender Systems (MORSs) emerged as a paradigm to guarantee multiple (often conflicting) goals. Besides accuracy, a MORS can operate at the global level, where additional beyond-accuracy goals are met for the system as a whole, or at the individual level, meaning that the recommendations are tailored to the needs of each user. The state-of-the-art MORSs either operate at the global or individual level, without assuming the co-existence of the two perspectives. In this study, we show that when global and individual objectives co-exist, MORSs are not able to meet both types of goals. To overcome this issue, we present an approach that regulates the recommendation lists so as to guarantee both global and individual perspectives, while preserving its effectiveness. Specifically, as individual perspective, we tackle genre calibration and, as global perspective, provider fairness. We validate our approach on two real-world datasets, publicly released with this paper.

翻译：多目标推荐系统（MORS）作为一种能够保证多个（通常相互冲突）目标的范式而出现。除了准确性之外，MORS可以在全局层面运行，此时系统整体满足额外的超越准确性的目标；也可以在个体层面运行，即推荐内容根据每个用户的需求定制。现有最先进的MORS要么在全局层面运行，要么在个体层面运行，未考虑两种视角的共存。在本研究中，我们证明当全局与个体目标共存时，MORS无法同时满足这两类目标。为解决这一问题，我们提出一种方法，该方法能够调节推荐列表以同时保障全局和个体视角，同时保持推荐的有效性。具体而言，个体视角方面我们处理类型校准问题，全局视角方面则处理提供者公平性问题。我们使用本文公开的两个真实世界数据集对所提方法进行了验证。