Masoud Mansoury

According to our database, Masoud Mansoury authored at least 36 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits.

Masoud Mansoury, Bamshad Mobasher, Herke van Hoof

CoRR, 2024

Beyond Static Calibration: The Impact of User Preference Dynamics on Calibrated Recommendation.

Kun Lin, Masoud Mansoury, Farzad Eskandanian, Milad Sabouri, Bamshad Mobasher

Proceedings of the Adjunct Proceedings of the 32nd ACM Conference on User Modeling, 2024

Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems.

Jin Huang, Harrie Oosterhuis, Masoud Mansoury, Herke van Hoof, Maarten de Rijke

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

SURE 2024: Workshop on Strategic and Utility-aware REcommendation.

Himan Abdollahpouri, Tonia Danylenko, Masoud Mansoury, Babak Loni, Daniel Russo, Mihajlo Grbovic

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Measuring Item Fairness in Next Basket Recommendation: A Reproducibility Study.

Yuanna Liu, Ming Li, Mozhdeh Ariannezhad, Masoud Mansoury, Mohammad Aliannejadi, Maarten de Rijke

Proceedings of the Advances in Information Retrieval, 2024

2023

Potential Factors Leading to Popularity Unfairness in Recommender Systems: A User-Centered Analysis.

Masoud Mansoury, Finn Duijvestijn, Imane Mourabet

CoRR, 2023

Fairness of Exposure in Dynamic Recommendation.

Masoud Mansoury, Bamshad Mobasher

CoRR, 2023

Career Path Recommendations for Long-term Income Maximization: A Reinforcement Learning Approach.

Spyros Avlonitis, Dor Lavi, Masoud Mansoury, David Graus

Proceedings of the 3rd Workshop on Recommender Systems for Human Resources (RecSys in HR 2023) co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

Predictive Uncertainty-based Bias Mitigation in Ranking.

Maria Heuss, Daniel Cohen, Masoud Mansoury, Maarten de Rijke, Carsten Eickhoff

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

A Graph-Based Approach for Mitigating Multi-Sided Exposure Bias in Recommender Systems.

Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke

ACM Trans. Inf. Syst., 2022

Understanding and mitigating multi-sided exposure bias in recommender systems.

Masoud Mansoury

SIGWEB Newsl., 2022

Exposure-Aware Recommendation using Contextual Bandits.

Masoud Mansoury, Bamshad Mobasher, Herke van Hoof

CoRR, 2022

MORS 2022: The Second Workshop on Multi-Objective Recommender Systems.

Himan Abdollahpouri, Shaghayegh Sahebi, Mehdi Elahi, Masoud Mansoury, Babak Loni, Zahra Nazari, Maria Dimakopoulou

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

2021

Flatter Is Better: Percentile Transformations for Recommender Systems.

Masoud Mansoury, Robin Burke, Bamshad Mobasher

ACM Trans. Intell. Syst. Technol., 2021

Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation.

Masoud Mansoury, Himan Abdollahpouri, Bamshad Mobasher, Mykola Pechenizkiy, Robin Burke, Milad Sabouri

CoRR, 2021

Fairness-Aware Recommendation in Multi-Sided Platforms.

Masoud Mansoury

Proceedings of the WSDM '21, 2021

Beyond Algorithmic Fairness in Recommender Systems.

Mehdi Elahi, Himan Abdollahpouri, Masoud Mansoury, Helma Torkamaan

Proceedings of the Adjunct Publication of the 29th ACM Conference on User Modeling, 2021

User-centered Evaluation of Popularity Bias in Recommender Systems.

Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher, Edward C. Malthouse

Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, 2021

MORS 2021 - 1st Workshop on Multi-Objective Recommender Systems.

Himan Abdollahpouri, Mehdi Elahi, Masoud Mansoury, Shaghayegh Sahebi, Zahra Nazari, Allison Chaney, Babak Loni

Proceedings of the 1st Workshop on Multi-Objective Recommender Systems (MORS 2021) co-located with 15th ACM Conference on Recommender Systems (RecSys 2021), 2021

librec-auto: A Tool for Recommender Systems Experimentation.

Nasim Sonboli, Masoud Mansoury, Ziyue Guo, Shreyas Kadekodi, Weiwen Liu, Zijun Liu, Andrew Schwartz, Robin Burke

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Addressing the Multistakeholder Impact of Popularity Bias in Recommendation Through Calibration.

Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher

CoRR, 2020

Multi-sided Exposure Bias in Recommendation.

Himan Abdollahpouri, Masoud Mansoury

CoRR, 2020

Unfair Exposure of Artists in Music Recommendation.

Himan Abdollahpouri, Robin Burke, Masoud Mansoury

CoRR, 2020

FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems.

Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization, 2020

Fairness-aware Recommendation with librec-auto.

Nasim Sonboli, Robin Burke, Zijun Liu, Masoud Mansoury

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation.

Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems.

Masoud Mansoury, Himan Abdollahpouri, Jessie Smith, Arman Dehpanah, Mykola Pechenizkiy, Bamshad Mobasher

Proceedings of the Thirty-Third International Florida Artificial Intelligence Research Society Conference, 2020

Experimentation with fairness-aware recommendation using librec-auto: hands-on tutorial.

Robin D. Burke, Masoud Mansoury, Nasim Sonboli

Proceedings of the FAT* '20: Conference on Fairness, 2020

Feedback Loop and Bias Amplification in Recommender Systems.

Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

The Relationship between the Consistency of Users' Ratings and Recommendation Calibration.

Masoud Mansoury, Himan Abdollahpouri, Joris Rombouts, Mykola Pechenizkiy

CoRR, 2019

The Impact of Popularity Bias on Fairness and Calibration in Recommendation.

Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher

CoRR, 2019

Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison.

Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy

Proceedings of the Workshop on Recommendation in Multi-stakeholder Environments co-located with the 13th ACM Conference on Recommender Systems (RecSys 2019), 2019

The Unfairness of Popularity Bias in Recommendation.

Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher

Proceedings of the Workshop on Recommendation in Multi-stakeholder Environments co-located with the 13th ACM Conference on Recommender Systems (RecSys 2019), 2019

Algorithm Selection with Librec-auto.

Masoud Mansoury, Robin Burke

Proceedings of the 1st Interdisciplinary Workshop on Algorithm Selection and Meta-Learning in Information Retrieval co-located with the 41st European Conference on Information Retrieval (ECIR 2019), 2019

2018

Automating recommender systems experimentation with librec-auto.

Masoud Mansoury, Robin Burke, Aldo Ordonez-Gauger, Xavier Sepulveda

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

2016

Improving recommender systems' performance on cold-start users and controversial items by a new similarity model.

Masoud Mansoury, Mehdi Shajari

Int. J. Web Inf. Syst., 2016