MultiFDF: Multi-Community Clustering for Fairness-Aware Recommendation-Reference-Cited by-同舟云学术

MultiFDF: Multi-Community Clustering for Fairness-Aware Recommendation

Published:2023-12 Issue:6 Volume:10 Page:2959-2970
ISSN:2329-924X
Container-title:IEEE Transactions on Computational Social Systems
language:
Short-container-title:IEEE Trans. Comput. Soc. Syst.

Author:

Wang Bang¹^ORCID,Song Shipeng²^ORCID,Liu Shenghao³^ORCID,Deng Xianjun³^ORCID

Affiliation:

1. Hubei Key Laboratory of Smart Internet Technology, School of Electronic Information and Communications, Huazhong University of Science and Technology (HUST), Wuhan, China

2. School of Electronic Information and Communications, Huazhong University of Science and Technology (HUST), Wuhan, China

3. Hubei Key Laboratory of Distributed System Security, Hubei Engineering Research Center on Big Data Security, School of Cyber Science and Engineering, Huazhong University of Science and Technology (HUST), Wuhan, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Human-Computer Interaction,Social Sciences (miscellaneous),Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/6570650/10352175/10145482.pdf?arnumber=10145482

Reference42 articles.

1. NeuronFair

2. GRIP-GAN: An Attack-Free Defense through General Robust Inverse Perturbation

3. MAG-GAN: Massive attack generator via GAN

4. Learning Fair Representations for Recommendation: A Graph-based Perspective

5. Controlling Popularity Bias in Learning-to-Rank Recommendation

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