12 citations · 16 across the 4 of their papers we have counts for
4 papers
A Personalized Framework for Consumer and Producer Group Fairness Optimization in Recommender Systems
Hossein A. Rahmani, Mohammadmehdi Naghiaei, Yashar Deldjoo
In recent years, there has been an increasing recognition that when machine learning (ML) algorithms are used to automate decisions, they may mistreat individuals or groups, with l…
Provider Fairness and Beyond-Accuracy Trade-offs in Recommender Systems
Saeedeh Karimi, Hossein A. Rahmani, Mohammadmehdi Naghiaei +1
Recommender systems, while transformative in online user experiences, have raised concerns over potential provider-side fairness issues. These systems may inadvertently favor popul…
Towards Confidence-aware Calibrated Recommendation
Mohammadmehdi Naghiaei, Hossein A. Rahmani, Mohammad Aliannejadi +1
Recommender systems utilize users' historical data to learn and predict their future interests, providing them with suggestions tailored to their tastes. Calibration ensures that t…
Exploring the Impact of Temporal Bias in Point-of-Interest Recommendation
Hossein A. Rahmani, Mohammadmehdi Naghiaei, Ali Tourani +1
Recommending appropriate travel destinations to consumers based on contextual information such as their check-in time and location is a primary objective of Point-of-Interest (POI)…