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)

Automating recommender systems experimentation with librec-auto. - Masoud Mansoury; Robin Burke; Aldo Ordonez-Gauger; Xavier Sepulveda (RecSys, 2018)

Algorithm Selection with Librec-auto. - Masoud Mansoury; Robin Burke (AMIR@ECIR, 2019)

The Unfairness of Popularity Bias in Recommendation. - Himan Abdollahpouri; Masoud Mansoury; Robin Burke; Bamshad Mobasher (RMSE@RecSys, 2019)

Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. - Masoud Mansoury; Bamshad Mobasher; Robin Burke; Mykola Pechenizkiy (RMSE@RecSys, 2019)

The Impact of Popularity Bias on Fairness and Calibration in Recommendation. - Himan Abdollahpouri; Masoud Mansoury; Robin Burke; Bamshad Mobasher (CoRR, 2019)

The Relationship between the Consistency of Users' Ratings and Recommendation Calibration. - Masoud Mansoury; Himan Abdollahpouri; Joris Rombouts; Mykola Pechenizkiy (CoRR, 2019)

Feedback Loop and Bias Amplification in Recommender Systems. - Masoud Mansoury; Himan Abdollahpouri; Mykola Pechenizkiy; Bamshad Mobasher; Robin Burke (CIKM, 2020)

Experimentation with fairness-aware recommendation using librec-auto: hands-on tutorial. - Robin D. Burke; Masoud Mansoury; Nasim Sonboli (FAT*, 2020)

Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems. - Masoud Mansoury; Himan Abdollahpouri; Jessie Smith; Arman Dehpanah; Mykola Pechenizkiy; Bamshad Mobasher (FLAIRS, 2020)

The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation. - Himan Abdollahpouri; Masoud Mansoury; Robin Burke; Bamshad Mobasher (RecSys, 2020)

Fairness-aware Recommendation with librec-auto. - Nasim Sonboli; Robin Burke; Zijun Liu; Masoud Mansoury (RecSys, 2020)

FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. - Masoud Mansoury; Himan Abdollahpouri; Mykola Pechenizkiy; Bamshad Mobasher; Robin Burke (UMAP, 2020)

Unfair Exposure of Artists in Music Recommendation. - Himan Abdollahpouri; Robin Burke; Masoud Mansoury (CoRR, 2020)

Multi-sided Exposure Bias in Recommendation. - Himan Abdollahpouri; Masoud Mansoury (CoRR, 2020)

Addressing the Multistakeholder Impact of Popularity Bias in Recommendation Through Calibration. - Himan Abdollahpouri; Masoud Mansoury; Robin Burke; Bamshad Mobasher (CoRR, 2020)

librec-auto: A Tool for Recommender Systems Experimentation. - Nasim Sonboli; Masoud Mansoury; Ziyue Guo; Shreyas Kadekodi; Weiwen Liu; Zijun Liu; Andrew Schwartz; Robin Burke (CIKM, 2021)

MORS 2021 - 1st Workshop on Multi-Objective Recommender Systems. - Himan Abdollahpouri; Mehdi Elahi; Masoud Mansoury; Shaghayegh Sahebi; Zahra Nazari; Allison Chaney; Babak Loni (MORS@RecSys, 2021)

User-centered Evaluation of Popularity Bias in Recommender Systems. - Himan Abdollahpouri; Masoud Mansoury; Robin Burke; Bamshad Mobasher; Edward C. Malthouse (UMAP, 2021)

Beyond Algorithmic Fairness in Recommender Systems. - Mehdi Elahi; Himan Abdollahpouri; Masoud Mansoury; Helma Torkamaan (UMAP (Adjunct Publication), 2021)

Fairness-Aware Recommendation in Multi-Sided Platforms. - Masoud Mansoury (WSDM, 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)

Flatter Is Better: Percentile Transformations for Recommender Systems. - Masoud Mansoury; Robin Burke; Bamshad Mobasher (ACM Trans. Intell. Syst. Technol., 2021)

MORS 2022: The Second Workshop on Multi-Objective Recommender Systems. - Himan Abdollahpouri; Shaghayegh Sahebi; Mehdi Elahi; Masoud Mansoury; Babak Loni; Zahra Nazari; Maria Dimakopoulou (RecSys, 2022)

Exposure-Aware Recommendation using Contextual Bandits. - Masoud Mansoury; Bamshad Mobasher; Herke van Hoof (CoRR, 2022)

Understanding and mitigating multi-sided exposure bias in recommender systems. - Masoud Mansoury (SIGWEB Newsl., 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)

Predictive Uncertainty-based Bias Mitigation in Ranking. - Maria Heuss; Daniel Cohen; Masoud Mansoury; Maarten de Rijke; Carsten Eickhoff (CIKM, 2023)

Career Path Recommendations for Long-term Income Maximization: A Reinforcement Learning Approach. - Spyros Avlonitis; Dor Lavi; Masoud Mansoury; David Graus (HR@RecSys, 2023)

Fairness of Exposure in Dynamic Recommendation. - Masoud Mansoury; Bamshad Mobasher (CoRR, 2023)

Potential Factors Leading to Popularity Unfairness in Recommender Systems: A User-Centered Analysis. - Masoud Mansoury; Finn Duijvestijn; Imane Mourabet (CoRR, 2023)

Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits. - Masoud Mansoury; Bamshad Mobasher; Herke van Hoof (CIKM, 2024)

Measuring Item Fairness in Next Basket Recommendation: A Reproducibility Study. - Yuanna Liu; Ming Li 068; Mozhdeh Ariannezhad; Masoud Mansoury; Mohammad Aliannejadi; Maarten de Rijke (ECIR (4), 2024)

SURE 2024: Workshop on Strategic and Utility-aware REcommendation. - Himan Abdollahpouri; Tonia Danylenko; Masoud Mansoury; Babak Loni; Daniel Russo 001; Mihajlo Grbovic (RecSys, 2024)

Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems. - Jin Huang 010; Harrie Oosterhuis; Masoud Mansoury; Herke van Hoof; Maarten de Rijke (SIGIR, 2024)

Beyond Static Calibration: The Impact of User Preference Dynamics on Calibrated Recommendation. - Kun Lin; Masoud Mansoury; Farzad Eskandanian; Milad Sabouri; Bamshad Mobasher (UMAP (Adjunct Publication), 2024)

Correcting for Popularity Bias in Recommender Systems via Item Loss Equalization. - Juno Prent; Masoud Mansoury (CoRR, 2024)

Towards Explainable Temporal User Profiling with LLMs. - Milad Sabouri; Masoud Mansoury; Kun Lin; Bamshad Mobasher (UMAP (Adjunct Publication), 2025)

Towards Carbon Footprint-Aware Recommender Systems for Greener Item Recommendation. - Raoul Kalisvaart; Masoud Mansoury; Alan Hanjalic; Elvin Isufi (CoRR, 2025)

A Reproducibility Study of Product-side Fairness in Bundle Recommendation. - Huy-Son Nguyen; Yuanna Liu; Masoud Mansoury; Mohammad Alian Nejadi; Alan Hanjalic; Maarten de Rijke (CoRR, 2025)

RaMen: Multi-Strategy Multi-Modal Learning for Bundle Construction. - Huy-Son Nguyen; Quang-Huy Nguyen; Duc-Hoang Pham; Duc-Trong Le; Hoang-Quynh Le; Padipat Sitkrongwong; Atsuhiro Takasu; Masoud Mansoury (CoRR, 2025)

Temporal User Profiling with LLMs: Balancing Short-Term and Long-Term Preferences for Recommendations. - Milad Sabouri; Masoud Mansoury; Kun Lin; Bamshad Mobasher (CoRR, 2025)

Using LLMs to Capture Users' Temporal Context for Recommendation. - Milad Sabouri; Masoud Mansoury; Kun Lin; Bamshad Mobasher (CoRR, 2025)

Mitigating Popularity Bias in Counterfactual Explanations using Large Language Models. - Arjan Hasami; Masoud Mansoury (CoRR, 2025)