Consumer-side Fairness in Recommender Systems: A Systematic Survey of Methods and Evaluation

16 May 2023

Papers citing "Consumer-side Fairness in Recommender Systems: A Systematic Survey of Methods and Evaluation"

7 / 7 papers shown

Title
Fair Augmentation for Graph Collaborative Filtering Ludovico Boratto Francesco Fabbri Gianni Fenu Mirko Marras Giacomo Medda 35 1 0 22 Aug 2024
Closing the Gender Wage Gap: Adversarial Fairness in Job Recommendation Clara Rus Jeffrey Luppes Harrie Oosterhuis Gido Schoenmacker FaML 24 12 0 20 Sep 2022
Fairness in Recommendation: Foundations, Methods and Applications Yunqi Li H. Chen Shuyuan Xu Yingqiang Ge Juntao Tan Shuchang Liu Yongfeng Zhang FaML OffRL 93 41 0 26 May 2022
Fairness in Recommender Systems: Research Landscape and Future Directions Yashar Deldjoo Dietmar Jannach Alejandro Bellogín Alessandro Difonzo Dario Zanzonelli OffRL FaML 86 82 0 23 May 2022
Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems A. Nikolakopoulos Xia Ning Christian Desrosiers George Karypis OffRL 30 28 0 09 Sep 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,143 0 23 Aug 2019
Learning Attitudes and Attributes from Multi-Aspect Reviews Julian McAuley J. Leskovec Dan Jurafsky 193 292 0 15 Oct 2012