197 citations · 228 across the 5 of their papers we have counts for
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FAIR: Fairness-Aware Information Retrieval Evaluation
Ruoyuan Gao, Yingqiang Ge, Chirag Shah
With the emerging needs of creating fairness-aware solutions for search and recommendation systems, a daunting challenge exists of evaluating such solutions. While many of the trad…
Towards Long-term Fairness in Recommendation
Yingqiang Ge, Shuchang Liu, Ruoyuan Gao +8
As Recommender Systems (RS) influence more and more people in their daily life, the issue of fairness in recommendation is becoming more and more important. Most of the prior appro…
University of Washington at TREC 2020 Fairness Ranking Track
Yunhe Feng, Daniel Saelid, Ke Li +2
InfoSeeking Lab's FATE (Fairness Accountability Transparency Ethics) group at University of Washington participated in 2020 TREC Fairness Ranking Track. This report describes that…
Facets of Fairness in Search and Recommendation
Sahil Verma, Ruoyuan Gao, Chirag Shah
Several recent works have highlighted how search and recommender systems exhibit bias along different dimensions. Counteracting this bias and bringing a certain amount of fairness…
Fairness-Aware Explainable Recommendation over Knowledge Graphs
Zuohui Fu, Yikun Xian, Ruoyuan Gao +8
There has been growing attention on fairness considerations recently, especially in the context of intelligent decision making systems. Explainable recommendation systems, in parti…