Constrained Off-policy Learning over Heterogeneous Information for Fairness-aware Recommendation

Fairness-aware recommendation eliminates discrimination issues to build trustworthy recommendation systems. Existing fairness-aware approaches ignore accounting for rich user and item attributes and thus cannot capture the impact of attributes on affecting recommendation fairness. These real-world a...

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Veröffentlicht in:	ACM transactions on recommender systems 2024-12, Vol.2 (4), p.1-27, Article 29
Hauptverfasser:	Wang, Xiangmeng, Li, Qian, Yu, Dianer, Li, Qing, Xu, Guandong
Format:	Artikel
Sprache:	eng
Schlagworte:	Information systems Recommender systems Reinforcement learning Theory of computation
Online-Zugang:	Volltext
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