User-oriented Fairness in Recommendation 摘要 对于一个高度数据驱动的app,推荐系统很容易被数据偏差影响,导致对不同数据组的不公平结果,同样这也是影响模型性能的重要原因。因此,如何定义并解决推荐系统场景下的不公平问题显得非常重要。 paper强调从user角度处理不公平问题,首先是按照他们活动的层次划分为优势组和劣势组...
Extensive experimental results demonstrate that the proposed method achieves better recommendation performance and fairness than the state-of-the-art methods. Moreover, user study results validates that the users' preferences captured via PRM are satisfactory, and UEM provides satisfactory POI ...