Author

Xiao-Feng Ding

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Review Open access Sep 2024

A Deep Dive into Fairness, Bias, Threats, and Privacy in Recommender Systems: Insights and Future Research

This study shows how algorithmic choices can unintentionally reinforce disparities, and reviews strategies for fair recommendation and privacy-preserving learning, and synthesizes current limitations and outline future directions to improve threat resilience, fairness and privacy.

Falguni Roy, Xiaofeng Ding, Kim-Kwang Raymond Choo et al. · ACM Computing Surveys · 4 citations

Review Open access Jul 2026

A Deep Dive into Fairness, Bias, Threats, and Privacy in Recommender Systems: Insights and Future Research

Recommender systems personalize digital experiences across e-commerce, streaming, and social media, yet they face linked challenges in fairness, bias, threats, and privacy. Bias can lead to unequal treatment, so fairness seeks equitable recommendations for all stakeholders. At the same time, adversarial attacks can ero...

Falguni Roy, Xiaofeng Ding, Kim-Kwang Raymond Choo · ACM Computing Surveys · 0 citations