Fairness Testing for Recommender Systems

The topic of fairness in recommender systems (RSs) is gaining significant attention. However, current fairness metrics and testing approaches primarily cater to classification systems and are not suitable for RSs. To bridge this gap, we aim to address the specific challenges involved in fairness testing for RSs. In this paper, we present a novel testing approach specifically designed for RSs, which enables us to achieve accurate results while maintaining high efficiency. Additionally, we suggest potential avenues for further research in the realm of fairness testing for RSs.