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2020 – today
- 2024
[c23]Yuanna Liu
, Ming Li, Mozhdeh Ariannezhad, Masoud Mansoury, Mohammad Aliannejadi, Maarten de Rijke:
Measuring Item Fairness in Next Basket Recommendation: A Reproducibility Study. ECIR (4) 2024: 210-225- [c22]Himan Abdollahpouri, Tonia Danylenko, Masoud Mansoury, Babak Loni, Daniel Russo, Mihajlo Grbovic:
SURE 2024: Workshop on Strategic and Utility-aware REcommendation. RecSys 2024: 1210-1212 - [c21]Jin Huang, Harrie Oosterhuis, Masoud Mansoury, Herke van Hoof, Maarten de Rijke:
Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems. SIGIR 2024: 416-426 - [c20]Kun Lin, Masoud Mansoury, Farzad Eskandanian, Milad Sabouri, Bamshad Mobasher:
Beyond Static Calibration: The Impact of User Preference Dynamics on Calibrated Recommendation. UMAP (Adjunct Publication) 2024 - [i24]Jin Huang, Harrie Oosterhuis, Masoud Mansoury, Herke van Hoof, Maarten de Rijke:
Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems. CoRR abs/2404.18640 (2024) - [i23]Kun Lin, Masoud Mansoury, Farzad Eskandanian, Milad Sabouri, Bamshad Mobasher:
Beyond Static Calibration: The Impact of User Preference Dynamics on Calibrated Recommendation. CoRR abs/2405.10232 (2024) - [i22]Masoud Mansoury, Bamshad Mobasher, Herke van Hoof:
Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits. CoRR abs/2408.04332 (2024) - 2023
- [c19]Maria Heuss, Daniel Cohen, Masoud Mansoury, Maarten de Rijke, Carsten Eickhoff:
Predictive Uncertainty-based Bias Mitigation in Ranking. CIKM 2023: 762-772 - [c18]Spyros Avlonitis, Dor Lavi, Masoud Mansoury, David Graus:
Career Path Recommendations for Long-term Income Maximization: A Reinforcement Learning Approach. HR@RecSys 2023 - [i21]Masoud Mansoury, Bamshad Mobasher:
Fairness of Exposure in Dynamic Recommendation. CoRR abs/2309.02322 (2023) - [i20]Spyros Avlonitis, Dor Lavi, Masoud Mansoury, David Graus:
Career Path Recommendations for Long-term Income Maximization: A Reinforcement Learning Approach. CoRR abs/2309.05391 (2023) - [i19]Maria Heuss, Daniel Cohen, Masoud Mansoury, Maarten de Rijke, Carsten Eickhoff:
Predictive Uncertainty-based Bias Mitigation in Ranking. CoRR abs/2309.09833 (2023) - [i18]Masoud Mansoury, Finn Duijvestijn, Imane Mourabet:
Potential Factors Leading to Popularity Unfairness in Recommender Systems: A User-Centered Analysis. CoRR abs/2310.02961 (2023) - 2022
- [j4]Masoud Mansoury:
Understanding and mitigating multi-sided exposure bias in recommender systems. SIGWEB Newsl. 2022(Autumn): 3:1-3:4 (2022) - [j3]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
A Graph-Based Approach for Mitigating Multi-Sided Exposure Bias in Recommender Systems. ACM Trans. Inf. Syst. 40(2): 32:1-32:31 (2022) - [c17]Himan Abdollahpouri, Shaghayegh Sahebi, Mehdi Elahi, Masoud Mansoury, Babak Loni, Zahra Nazari, Maria Dimakopoulou:
MORS 2022: The Second Workshop on Multi-Objective Recommender Systems. RecSys 2022: 658-660 - [e2]Himan Abdollahpouri, Shaghayegh Sahebi, Mehdi Elahi, Masoud Mansoury, Babak Loni, Zahra Nazari, Maria Dimakopoulou:
Proceedings of the 2nd Workshop on Multi-Objective Recommender Systems co-located with 16th ACM Conference on Recommender Systems (RecSys 2022), Seattle, WA, USA, 18th-23rd September 2022. CEUR Workshop Proceedings 3268, CEUR-WS.org 2022 [contents] - [i17]Masoud Mansoury, Bamshad Mobasher, Herke van Hoof:
Exposure-Aware Recommendation using Contextual Bandits. CoRR abs/2209.01665 (2022) - 2021
- [j2]Masoud Mansoury, Robin Burke, Bamshad Mobasher:
Flatter Is Better: Percentile Transformations for Recommender Systems. ACM Trans. Intell. Syst. Technol. 12(2): 19:1-19:16 (2021) - [c16]Nasim Sonboli, Masoud Mansoury, Ziyue Guo, Shreyas Kadekodi, Weiwen Liu, Zijun Liu, Andrew Schwartz, Robin Burke:
librec-auto: A Tool for Recommender Systems Experimentation. CIKM 2021: 4584-4593 - [c15]Himan Abdollahpouri, Mehdi Elahi, Masoud Mansoury, Shaghayegh Sahebi, Zahra Nazari, Allison Chaney, Babak Loni:
MORS 2021: 1st Workshop on Multi-Objective Recommender Systems. RecSys 2021: 787-788 - [c14]Himan Abdollahpouri, Mehdi Elahi, Masoud Mansoury, Shaghayegh Sahebi, Zahra Nazari, Allison Chaney, Babak Loni:
MORS 2021 - 1st Workshop on Multi-Objective Recommender Systems. MORS@RecSys 2021 - [c13]Mehdi Elahi, Himan Abdollahpouri, Masoud Mansoury, Helma Torkamaan:
Beyond Algorithmic Fairness in Recommender Systems. UMAP (Adjunct Publication) 2021: 41-46 - [c12]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher, Edward C. Malthouse:
User-centered Evaluation of Popularity Bias in Recommender Systems. UMAP 2021: 119-129 - [c11]Masoud Mansoury:
Fairness-Aware Recommendation in Multi-Sided Platforms. WSDM 2021: 1117-1118 - [e1]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), Amsterdam, The Netherlands, September 25, 2021. CEUR Workshop Proceedings 2959, CEUR-WS.org 2021 [contents] - [i16]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher, Edward C. Malthouse:
User-centered Evaluation of Popularity Bias in Recommender Systems. CoRR abs/2103.06364 (2021) - [i15]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
A Graph-based Approach for Mitigating Multi-sided Exposure Bias in Recommender Systems. CoRR abs/2107.03415 (2021) - [i14]Masoud Mansoury, Himan Abdollahpouri, Bamshad Mobasher, Mykola Pechenizkiy, Robin Burke, Milad Sabouri:
Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation. CoRR abs/2108.03440 (2021) - [i13]Masoud Mansoury:
Understanding and Mitigating Multi-Sided Exposure Bias in Recommender Systems. CoRR abs/2111.05564 (2021) - 2020
- [c10]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
Feedback Loop and Bias Amplification in Recommender Systems. CIKM 2020: 2145-2148 - [c9]Robin D. Burke, Masoud Mansoury, Nasim Sonboli:
Experimentation with fairness-aware recommendation using librec-auto: hands-on tutorial. FAT* 2020: 700 - [c8]Masoud Mansoury, Himan Abdollahpouri, Jessie Smith, Arman Dehpanah, Mykola Pechenizkiy, Bamshad Mobasher:
Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems. FLAIRS 2020: 193-196 - [c7]Nasim Sonboli, Robin Burke, Zijun Liu, Masoud Mansoury:
Fairness-aware Recommendation with librec-auto. RecSys 2020: 594-596 - [c6]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation. RecSys 2020: 726-731 - [c5]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. UMAP 2020: 154-162 - [i12]Masoud Mansoury, Himan Abdollahpouri, Jessie Smith, Arman Dehpanah, Mykola Pechenizkiy, Bamshad Mobasher:
Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems. CoRR abs/2002.07786 (2020) - [i11]Himan Abdollahpouri, Robin Burke, Masoud Mansoury:
Unfair Exposure of Artists in Music Recommendation. CoRR abs/2003.11634 (2020) - [i10]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. CoRR abs/2005.01148 (2020) - [i9]Himan Abdollahpouri, Masoud Mansoury:
Multi-sided Exposure Bias in Recommendation. CoRR abs/2006.15772 (2020) - [i8]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
Addressing the Multistakeholder Impact of Popularity Bias in Recommendation Through Calibration. CoRR abs/2007.12230 (2020) - [i7]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
Feedback Loop and Bias Amplification in Recommender Systems. CoRR abs/2007.13019 (2020) - [i6]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation. CoRR abs/2008.09273 (2020)
2010 – 2019
- 2019
- [c4]Masoud Mansoury, Robin Burke:
Algorithm Selection with Librec-auto. AMIR@ECIR 2019: 11-17 - [c3]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
The Unfairness of Popularity Bias in Recommendation. RMSE@RecSys 2019 - [c2]Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy:
Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. RMSE@RecSys 2019 - [i5]Masoud Mansoury, Robin Burke, Bamshad Mobasher:
Flatter is better: Percentile Transformations for Recommender Systems. CoRR abs/1907.07766 (2019) - [i4]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
The Unfairness of Popularity Bias in Recommendation. CoRR abs/1907.13286 (2019) - [i3]Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy:
Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. CoRR abs/1908.00831 (2019) - [i2]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
The Impact of Popularity Bias on Fairness and Calibration in Recommendation. CoRR abs/1910.05755 (2019) - [i1]Masoud Mansoury, Himan Abdollahpouri, Joris Rombouts, Mykola Pechenizkiy:
The Relationship between the Consistency of Users' Ratings and Recommendation Calibration. CoRR abs/1911.00852 (2019) - 2018
- [c1]Masoud Mansoury, Robin Burke, Aldo Ordonez-Gauger, Xavier Sepulveda:
Automating recommender systems experimentation with librec-auto. RecSys 2018: 500-501 - 2016
- [j1]Masoud Mansoury, Mehdi Shajari:
Improving recommender systems' performance on cold-start users and controversial items by a new similarity model. Int. J. Web Inf. Syst. 12(2): 126-149 (2016)
Coauthor Index
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last updated on 2024-10-23 21:27 CEST by the dblp team
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