FAIR: Fairness-Aware Information Retrieval Evaluation

no code implementations • 16 Jun 2021 • Ruoyuan Gao, Yingqiang Ge, Chirag Shah

We believe our work opens up a new direction of pursuing a metric for evaluating and implementing the FAIR systems.

Fairness Information Retrieval +2

Towards Long-term Fairness in Recommendation

1 code implementation • 10 Jan 2021 • Yingqiang Ge, Shuchang Liu, Ruoyuan Gao, Yikun Xian, Yunqi Li, Xiangyu Zhao, Changhua Pei, Fei Sun, Junfeng Ge, Wenwu Ou, Yongfeng Zhang

We focus on the fairness of exposure of items in different groups, while the division of the groups is based on item popularity, which dynamically changes over time in the recommendation process.

Fairness Recommendation Systems

University of Washington at TREC 2020 Fairness Ranking Track

no code implementations • 3 Nov 2020 • Yunhe Feng, Daniel Saelid, Ke Li, Ruoyuan Gao, Chirag Shah

The results showed that our runs performed below par for re-ranking task, but above average for retrieval.

Ethics Fairness +2

Facets of Fairness in Search and Recommendation

no code implementations • 16 Jul 2020 • Sahil Verma, Ruoyuan Gao, Chirag Shah

Several recent works have highlighted how search and recommender systems exhibit bias along different dimensions.

Fairness Recommendation Systems

Fairness-Aware Explainable Recommendation over Knowledge Graphs

no code implementations • 3 Jun 2020 • Zuohui Fu, Yikun Xian, Ruoyuan Gao, Jieyu Zhao, Qiaoying Huang, Yingqiang Ge, Shuyuan Xu, Shijie Geng, Chirag Shah, Yongfeng Zhang, Gerard de Melo

There has been growing attention on fairness considerations recently, especially in the context of intelligent decision making systems.

Collaborative Filtering Decision Making +5

Learning to Interpret Natural Language Instructions

no code implementations • WS 2012 • Monica Babe{\c{s}}-Vroman, James Macglashan, Ruoyuan Gao, Kevin Winner, Richard Adjogah, Marie desJardins, Michael Littman, Smar Muresan, a

Language Modelling Semantic Parsing