Mohammadmehdi Naghiaei

Orcid: 0000-0003-1667-2779

According to our database1, Mohammadmehdi Naghiaei authored at least 13 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2024
A Personalized Framework for Consumer and Producer Group Fairness Optimization in Recommender Systems.
Trans. Recomm. Syst., September, 2024

CAPRI: Context-aware point-of-interest recommendation framework.
Softw. Impacts, 2024

Personalized Beyond-accuracy Calibration in Recommendation.
Proceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval, 2024

Clarifying the Path to User Satisfaction: An Investigation into Clarification Usefulness.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

2023
Provider Fairness and Beyond-Accuracy Trade-offs in Recommender Systems.
CoRR, 2023

CAPRI: Context-Aware Interpretable Point-of-Interest Recommendation Framework.
CoRR, 2023

2022
PyCPFair: A framework for consumer and producer fairness in recommender systems.
Softw. Impacts, 2022

Experiments on Generalizability of User-Oriented Fairness in Recommender Systems.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Exploring the Impact of Temporal Bias in Point-of-Interest Recommendation.
Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Towards Confidence-aware Calibrated Recommendation.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

The Unfairness of Active Users and Popularity Bias in Point-of-Interest Recommendation.
Proceedings of the Advances in Bias and Fairness in Information Retrieval, 2022

The Unfairness of Popularity Bias in Book Recommendation.
Proceedings of the Advances in Bias and Fairness in Information Retrieval, 2022


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