28 citations · 78 across the 23 of their papers we have counts for
9 papers · 1 filter
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)…
ViralBERT: A User Focused BERT-Based Approach to Virality Prediction
Rikaz Rameez, Hossein A. Rahmani, Emine Yilmaz
Recently, Twitter has become the social network of choice for sharing and spreading information to a multitude of users through posts called 'tweets'. Users can easily re-share the…
Experiments on Generalizability of User-Oriented Fairness in Recommender Systems
Hossein A. Rahmani, Mohammadmehdi Naghiaei, Mahdi Dehghan +1
Recent work in recommender systems mainly focuses on fairness in recommendations as an important aspect of measuring recommendations quality. A fairness-aware recommender system ai…
CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems
Mohammadmehdi Naghiaei, Hossein A. Rahmani, Yashar Deldjoo
Recently, there has been a rising awareness that when machine learning (ML) algorithms are used to automate choices, they may treat/affect individuals unfairly, with legal, ethical…
The Unfairness of Popularity Bias in Book Recommendation
Mohammadmehdi Naghiaei, Hossein A. Rahmani, Mahdi Dehghan
Recent studies have shown that recommendation systems commonly suffer from popularity bias. Popularity bias refers to the problem that popular items (i.e., frequently rated items)…
The Unfairness of Active Users and Popularity Bias in Point-of-Interest Recommendation
Hossein A. Rahmani, Yashar Deldjoo, Ali Tourani +1
Point-of-Interest (POI) recommender systems provide personalized recommendations to users and help businesses attract potential customers. Despite their success, recent studies sug…
A Systematic Analysis on the Impact of Contextual Information on Point-of-Interest Recommendation
Hossein A. Rahmani, Mohammad Aliannejadi, Mitra Baratchi +1
As the popularity of Location-based Social Networks (LBSNs) increases, designing accurate models for Point-of-Interest (POI) recommendation receives more attention. POI recommendat…
Leveraging Social Influence based on Users Activity Centers for Point-of-Interest Recommendation
Kosar Seyedhoseinzadeh, Hossein A. Rahmani, Mohsen Afsharchi +1
Recommender Systems (RSs) aim to model and predict the user preference while interacting with items, such as Points of Interest (POIs). These systems face several challenges, such…