Nasim Sonboli

According to our database, Nasim Sonboli authored at least 25 papers between 2018 and 2023.

Collaborative distances:

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

2023

FAccTRec 2023: The 6th Workshop on Responsible Recommendation.

Michael D. Ekstrand, Jean Garcia-Gathright, Nasim Sonboli, Amifa Raj, Karlijn Dinnissen

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

2022

The Multisided Complexity of Fairness in Recommender Systems.

Nasim Sonboli, Robin Burke, Michael D. Ekstrand, Rishabh Mehrotra

AI Mag., 2022

5th Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2022).

Styliani Kleanthous, Bamshad Mobasher, Tsvika Kuflik, Bettina Berendt, Robin Burke, Jahna Otterbacher, Nasim Sonboli, Avital Shulner-Tal

Proceedings of the UMAP '22: 30th ACM Conference on User Modeling, Adaptation and Personalization, Barcelona, Spain, July 4, 2022

Multi-agent Social Choice for Dynamic Fairness-aware Recommendation.

Robin Burke, Nicholas Mattei, Vladislav Grozin, Amy Voida, Nasim Sonboli

Proceedings of the UMAP '22: 30th ACM Conference on User Modeling, Adaptation and Personalization, Barcelona, Spain, July 4, 2022

FAccTRec 2022: The 5th Workshop on Responsible Recommendation.

Nasim Sonboli, Toshihiro Kamishima, Amifa Raj, Luca Belli, Robin Burke

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

Towards Confidence-aware Calibrated Recommendation.

Mohammadmehdi Naghiaei, Hossein A. Rahmani, Mohammad Aliannejadi, Nasim Sonboli

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Fairness and Transparency in Recommendation: The Users' Perspective.

Nasim Sonboli, Jessie J. Smith, Florencia Cabral Berenfus, Robin Burke, Casey Fiesler

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

FAccTRec 2021: The 4th Workshop on Responsible Recommendation.

Michael D. Ekstrand, Pierre-Nicolas Schwab, Toshihiro Kamishima, Nasim Sonboli

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 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

"And the Winner Is...": Dynamic Lotteries for Multi-group Fairness-Aware Recommendation.

Nasim Sonboli, Robin Burke, Nicholas Mattei, Farzad Eskandanian, Tian Gao

CoRR, 2020

Exploring User Opinions of Fairness in Recommender Systems.

Jessie Smith, Nasim Sonboli, Casey Fiesler, Robin Burke

CoRR, 2020

Using Social Tag Embedding in a Collaborative Filtering Approach for Recommender Systems.

Diego Sánchez-Moreno, María N. Moreno García, Nasim Sonboli, Bamshad Mobasher, Robin Burke

Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2020

Opportunistic Multi-aspect Fairness through Personalized Re-ranking.

Nasim Sonboli, Farzad Eskandanian, Robin Burke, Weiwen Liu, Bamshad Mobasher

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

3rd FAccTRec Workshop: Responsible Recommendation.

Michael D. Ekstrand, Pierre-Nicolas Schwab, Jean Garcia-Gathright, Toshihiro Kamishima, Nasim Sonboli

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

Calibration in Collaborative Filtering Recommender Systems: a User-Centered Analysis.

Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke

Proceedings of the HT '20: 31st ACM Conference on Hypertext and Social Media, 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

2019

Data Science Summer Academy for Chicago Public School Students.

Bamshad Mobasher, Lucia Dettori, Daniela Raicu, Raffaella Settimi, Nasim Sonboli, Monica Stettler

SIGKDD Explor., 2019

Localized Fairness in Recommender Systems.

Nasim Sonboli, Robin Burke

Proceedings of the Adjunct Publication of the 27th Conference on User Modeling, 2019

Power of the Few: Analyzing the Impact of Influential Users in Collaborative Recommender Systems.

Farzad Eskandanian, Nasim Sonboli, Bamshad Mobasher

Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization, 2019

Personalized fairness-aware re-ranking for microlending.

Weiwen Liu, Jun Guo, Nasim Sonboli, Robin Burke, Shengyu Zhang

Proceedings of the 13th ACM Conference on Recommender Systems, 2019

Crank up the Volume: Preference Bias Amplification in Collaborative Recommendation.

Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke

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

2018

Synthetic Attribute Data for Evaluating Consumer-side Fairness.

Robin Burke, Jackson Kontny, Nasim Sonboli

CoRR, 2018

Inferring User Expertise from Social Tagging in Music Recommender Systems for Streaming Services.

Diego Sánchez-Moreno, María N. Moreno García, Nasim Sonboli, Bamshad Mobasher, Robin Burke

Proceedings of the Hybrid Artificial Intelligent Systems - 13th International Conference, 2018

Balanced Neighborhoods for Multi-sided Fairness in Recommendation.

Robin Burke, Nasim Sonboli, Aldo Ordonez-Gauger

Proceedings of the Conference on Fairness, Accountability and Transparency, 2018