Proportional Ranking

Proportional ranking aims to create ranked lists that fairly represent different groups, addressing biases that can arise in applications like recommender systems and election processes. Current research focuses on developing algorithms, such as those based on the Sinkhorn algorithm or minimax optimization, that efficiently achieve various fairness criteria, including proportional representation of groups defined by multiple attributes. This work is significant because it tackles the ethical and practical challenges of biased ranking in numerous domains, improving both the fairness and utility of ranking systems.