ProFairRec

Author:

Qi Tao1,Wu Fangzhao2,Wu Chuhan1,Sun Peijie3,Wu Le3,Wang Xiting2,Huang Yongfeng1,Xie Xing2

Affiliation:

1. Tsinghua University, Beijing, China

2. Microsoft Research Asia, Beijing, China

3. Hefei University of Technology, Hefei, China

Funder

National Natural Science Foundation of China

Tsinghua-Toyota Joint Research Fund

Publisher

ACM

Reference58 articles.

1. Mingxiao An Fangzhao Wu Chuhan Wu Kun Zhang Zheng Liu and Xing Xie. 2019. Neural news recommendation with long-and short-term user representations. In ACL . 336--345. Mingxiao An Fangzhao Wu Chuhan Wu Kun Zhang Zheng Liu and Xing Xie. 2019. Neural news recommendation with long-and short-term user representations. In ACL . 336--345.

2. Trapit Bansal Mrinal Das and Chiranjib Bhattacharyya. 2015. Content driven user profiling for comment-worthy recommendations of news and blog articles. In RecSys. 195--202. Trapit Bansal Mrinal Das and Chiranjib Bhattacharyya. 2015. Content driven user profiling for comment-worthy recommendations of news and blog articles. In RecSys. 195--202.

3. Robin Burke Nasim Sonboli and Aldo Ordonez-Gauger. 2018. Balanced neighborhoods for multi-sided fairness in recommendation. In ACM FAccT . 202--214. Robin Burke Nasim Sonboli and Aldo Ordonez-Gauger. 2018. Balanced neighborhoods for multi-sided fairness in recommendation. In ACM FAccT . 202--214.

4. Abhinandan S Das Mayur Datar Ashutosh Garg and Shyam Rajaram. 2007. Google news personalization: scalable online collaborative filtering. In WWW . 271--280. Abhinandan S Das Mayur Datar Ashutosh Garg and Shyam Rajaram. 2007. Google news personalization: scalable online collaborative filtering. In WWW . 271--280.

5. Suyu Ge Chuhan Wu Fangzhao Wu Tao Qi and Yongfeng Huang. 2020. Graph enhanced representation learning for news recommendation. In WWW . 2863--2869. Suyu Ge Chuhan Wu Fangzhao Wu Tao Qi and Yongfeng Huang. 2020. Graph enhanced representation learning for news recommendation. In WWW . 2863--2869.

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1. Unbiased news recommendation model combining time and content;Expert Systems with Applications;2024-12

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3. LTP-MMF: Towards Long-term Provider Max-min Fairness Under Recommendation Feedback Loops;ACM Transactions on Information Systems;2024-09-13

4. A Hierarchical and Disentangling Interest Learning Framework for Unbiased and True News Recommendation;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

5. Dual-Side Adversarial Learning Based Fair Recommendation for Sensitive Attribute Filtering;ACM Transactions on Knowledge Discovery from Data;2024-06-19

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