Fairness in recommender systems: research landscape and future directions

Y Deldjoo, D Jannach, A Bellogin, A Difonzo… - User Modeling and User …, 2024 - Springer
Recommender systems can strongly influence which information we see online, eg, on
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …

A comprehensive survey on trustworthy recommender systems

W Fan, X Zhao, X Chen, J Su, J Gao, L Wang… - arXiv preprint arXiv …, 2022 - arxiv.org
As one of the most successful AI-powered applications, recommender systems aim to help
people make appropriate decisions in an effective and efficient way, by providing …

A survey on the fairness of recommender systems

Y Wang, W Ma, M Zhang, Y Liu, S Ma - ACM Transactions on …, 2023 - dl.acm.org
Recommender systems are an essential tool to relieve the information overload challenge
and play an important role in people's daily lives. Since recommendations involve …

Fairness in graph mining: A survey

Y Dong, J Ma, S Wang, C Chen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Graph mining algorithms have been playing a significant role in myriad fields over the years.
However, despite their promising performance on various graph analytical tasks, most of …

Fairness in information access systems

MD Ekstrand, A Das, R Burke… - Foundations and Trends …, 2022 - nowpublishers.com
Recommendation, information retrieval, and other information access systems pose unique
challenges for investigating and applying the fairness and non-discrimination concepts that …

Fairness in recommendation: A survey

Y Li, H Chen, S Xu, Y Ge, J Tan, S Liu… - arXiv preprint arXiv …, 2022 - arxiv.org
As one of the most pervasive applications of machine learning, recommender systems are
playing an important role on assisting human decision making. The satisfaction of users and …

Fairness in recommendation: Foundations, methods, and applications

Y Li, H Chen, S Xu, Y Ge, J Tan, S Liu… - ACM Transactions on …, 2023 - dl.acm.org
As one of the most pervasive applications of machine learning, recommender systems are
playing an important role on assisting human decision-making. The satisfaction of users and …

Mitigating bias in algorithmic systems—a fish-eye view

K Orphanou, J Otterbacher, S Kleanthous… - ACM Computing …, 2022 - dl.acm.org
Mitigating bias in algorithmic systems is a critical issue drawing attention across
communities within the information and computer sciences. Given the complexity of the …

[HTML][HTML] SQUIRREL: A framework for sequential group recommendations through reinforcement learning

M Stratigi, E Pitoura, K Stefanidis - Information Systems, 2023 - Elsevier
Nowadays, sequential recommendations are becoming more prevalent. A user expects the
system to remember past interactions and not conduct each recommendation round as a …

[HTML][HTML] A personality-aware group recommendation system based on pairwise preferences

R Abolghasemi, P Engelstad, E Herrera-Viedma… - Information …, 2022 - Elsevier
Human personality plays a crucial role in decision-making and it has paramount importance
when individuals negotiate with each other to reach a common group decision. Such …