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Ruoyuan Gao
Ruoyuan Gao
Verified email at rutgers.edu - Homepage
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Year
Fairness-aware explainable recommendation over knowledge graphs
Z Fu, Y Xian, R Gao, J Zhao, Q Huang, Y Ge, S Xu, S Geng, C Shah, ...
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
2022020
Towards Long-term Fairness in Recommendation
Y Ge, S Liu, R Gao, Y Xian, Y Li, X Zhao, C Pei, F Sun, J Ge, W Ou, ...
Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021
1872021
Toward creating a fairer ranking in search engine results
R Gao, C Shah
Information Processing & Management 57 (1), 102138, 2020
1112020
How Fair Can We Go: Detecting the Boundaries of Fairness Optimization in Information Retrieval
R Gao, C Shah
Proceedings of the 2019 ACM SIGIR International Conference on Theory of …, 2019
352019
Counteracting bias and increasing fairness in search and recommender systems
R Gao, C Shah
Proceedings of the 14th ACM Conference on Recommender Systems, 745-747, 2020
262020
FAIR: Fairness-Aware Information Retrieval Evaluation
R Gao, Y Ge, C Shah
Journal of the Association for Information Science and Technology (JASIST), 2022
252022
Addressing Bias and Fairness in Search Systems
R Gao, C Shah
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
242021
Facets of fairness in search and recommendation
S Verma, R Gao, C Shah
Bias and Social Aspects in Search and Recommendation: First International …, 2020
182020
Learning to interpret natural language instructions
M Babes-Vroman, J MacGlashan, R Gao, K Winner, R Adjogah, M Littman, ...
Proceedings of the Second Workshop on Semantic Interpretation in an …, 2012
10*2012
Toward a fairer information retrieval system
R Gao
ACM SIGIR Forum 55 (1), 1-2, 2021
42021
University of Washington at TREC 2020 Fairness Ranking Track
Y Feng, D Saelid, K Li, R Gao, C Shah
arXiv preprint arXiv:2011.02066, 2020
42020
Towards Fairness-Aware Ranking by Defining Latent Groups Using Inferred Features
Y Feng, D Saelid, K Li, R Gao, C Shah
BIAS@ECIR 2021 Workshop, 0
4*
Learning to interpret natural language instructions
J MacGlashan, M Babes-Vroman, K Winner, R Gao, R Adjogah, M Littman, ...
Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012
22012
Using an integrated feature set to generalize and justify the Chinese-to-English transferring rule of the ‘ZHE’aspect
Y Qu, T Tao, S Sharoff, N Jin, R Gao, N Zhang, Y Yang, C Xu
Journal of Zhejiang University SCIENCE C 11, 663-676, 2010
12010
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Articles 1–14