12 citations · 50 across the 21 of their papers we have counts for
17 papers · 1 filter
Clarifying the Path to User Satisfaction: An Investigation into Clarification Usefulness
Hossein A. Rahmani, Xi Wang, Mohammad Aliannejadi +2
Clarifying questions are an integral component of modern information retrieval systems, directly impacting user satisfaction and overall system performance. Poorly formulated quest…
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…
CAPRI: Context-Aware Interpretable Point-of-Interest Recommendation Framework
Ali Tourani, Hossein A. Rahmani, Mohammadmehdi Naghiaei +1
Point-of-Interest (POI ) recommendation systems have gained popularity for their unique ability to suggest geographical destinations with the incorporation of contextual informatio…
A Survey on Asking Clarification Questions Datasets in Conversational Systems
Hossein A. Rahmani, Xi Wang, Yue Feng +3
The ability to understand a user's underlying needs is critical for conversational systems, especially with limited input from users in a conversation. Thus, in such a domain, Aski…
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)…