Robin Burke - RankMe

131 papers A* 2A 26Misc 2Journal 57Unranked 36

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	7th UMAP Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2025). UMAP (Adjunct Publication) Bamshad Mobasher, Styliani Kleanthous, Robin Burke, Avital Shulner-Tal, Tsvi Kuflik
2025	—	`conf`	Conducting Recommender Systems User Studies Using POPROX. UMAP (Adjunct Publication) Robin Burke, Michael D. Ekstrand
2025	J	`jnl`	De-centering the (Traditional) User: Multistakeholder Evaluation of Recommender Systems. CoRR Robin Burke, Gediminas Adomavicius, Toine Bogers, Tommaso Di Noia, Dominik Kowald, Julia Neidhardt, Özlem Özgöbek, Maria Soledad Pera, Nava Tintarev, Jürgen Ziegler
2025	J	`jnl`	De-centering the (Traditional) user: Multistakeholder evaluation of recommender systems. Int. J. Hum. Comput. Stud. Robin Burke, Gediminas Adomavicius, Toine Bogers, Tommaso Di Noia, Dominik Kowald, Julia Neidhardt, Özlem Özgöbek, Maria Soledad Pera, Nava Tintarev, Jürgen Ziegler
2025	J	`jnl`	Decoupled Recommender Systems: Exploring Alternative Recommender Ecosystem Designs. CoRR Anas Buhayh, Elizabeth McKinnie, Robin Burke
2025	J	`jnl`	Dynamic Fairness-aware Recommendation Through Multi-agent Social Choice. Trans. Recomm. Syst. Amanda Aird, Paresha Farastu, Joshua Sun, Elena Stefancova, Cassidy All, Amy Voida, Nicholas Mattei, Robin Burke
2025	J	`jnl`	Envy-Free but Still Unfair: Envy-Freeness Up To One Item (EF-1) in Personalized Recommendation. CoRR Amanda Aird, Ben Armstrong, Nicholas Mattei, Robin Burke
2025	J	`jnl`	Fairness for niche users and providers: algorithmic choice and profile portability. CoRR Elizabeth McKinnie, Anas Buhayh, Clement Canel, Robin Burke
2025	A	`conf`	Integrating Individual and Group Fairness for Recommender Systems through Social Choice. RecSys Amanda Aird, Elena Stefancova, Anas Buhayh, Cassidy All, Martin Homola, Nicholas Mattei, Robin Burke
2025	—	`conf`	Pragmatic Fairness: Evaluating ML Fairness Within the Constraints of Industry. FAccT Jessie J. Smith, Michael Madaio, Robin Burke, Casey Fiesler
2025	A	`conf`	Proposal for Workshop on Trust and Responsibility in Recommendation Systems at WSDM 2025. WSDM Xinghai Hu, Robin Burke, Xu Liu
2025	J	`jnl`	Recommending With, Not For: Co-Designing Recommender Systems for Social Good. CoRR Michael D. Ekstrand, Afsaneh Razi, Aleksandra Sarcevic, Maria Soledad Pera, Robin Burke, Katherine Landau Wright
2025	—	`conf`	Simulating the Algorithm Store: Multistakeholder Impacts of Recommender Choice. UMAP (Adjunct Publication) Anas Buhayh, Elizabeth McKinnie, Clement Canel, Robin Burke
2025	J	`jnl`	What News Recommendation Research Did (But Mostly Didn't) Teach Us About Building A News Recommender. CoRR Karl Higley, Robin Burke, Michael D. Ekstrand, Bart P. Knijnenburg
2024	—	`conf`	Comparative Explanations for Recommendation: Research Directions. IntRS@RecSys Meysam Varasteh, Elizabeth McKinnie, Amanda Aird, Daniel E. Acuña, Robin Burke
2024	A	`conf`	Conducting Recommender Systems User Studies Using POPROX. RecSys Robin Burke, Joseph A. Konstan, Michael D. Ekstrand
2024	J	`jnl`	Data Generation via Latent Factor Simulation for Fairness-aware Re-ranking. CoRR Elena Stefancova, Cassidy All, Joshua Paup, Martin Homola, Nicholas Mattei, Robin Burke
2024	—	`conf`	Decoupled Recommender Systems: Exploring Alternative Recommender Ecosystem Designs. RecSoGood@RecSys Anas Buhayh, Elizabeth McKinnie, Robin Burke
2024	J	`jnl`	Post-Userist Recommender Systems : A Manifesto. CoRR Robin Burke, Morgan Sylvester
2024	J	`jnl`	RecSOI: recommending research directions using statements of ignorance. J. Biomed. Semant. Adrien Bibal, Nourah M. Salem, Rémi Cardon, Elizabeth K. White, Daniel E. Acuna, Robin Burke, Lawrence E. Hunter
2024	—	`conf`	Recommend Me? Designing Fairness Metrics with Providers. FAccT Jessie J. Smith, Aishwarya Satwani, Robin Burke, Casey Fiesler
2024	A	`conf`	Social Choice for Heterogeneous Fairness in Recommendation. RecSys Amanda Aird, Elena Stefancova, Cassidy All, Amy Voida, Martin Homola, Nicholas Mattei, Robin Burke
2024	J	`jnl`	Social Choice for Heterogeneous Fairness in Recommendation. CoRR Amanda Aird, Elena Stefancova, Cassidy All, Amy Voida, Martin Homola, Nicholas Mattei, Robin Burke
2023	—	`conf`	"It's just a robot that looks at numbers": Restoring Journalistic Voice in News Recommendation. INRA@RecSys Nihal Alaqabawy, Aishwarya Satwani, Amy Voida, Robin Burke
2023	—	`conf`	6th Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2023). UMAP (Adjunct Publication) Bamshad Mobasher, Styliani Kleanthous, Jahna Otterbacher, Robin Burke, Avital Shulner-Tal
2023	J	`jnl`	Dynamic fairness-aware recommendation through multi-agent social choice. CoRR Amanda Aird, Paresha Farastu, Joshua Sun, Amy Voida, Nicholas Mattei, Robin Burke
2023	J	`jnl`	Exploring Social Choice Mechanisms for Recommendation Fairness in SCRUF. CoRR Amanda Aird, Cassidy All, Paresha Farastu, Elena Stefancova, Joshua Sun, Nicholas Mattei, Robin Burke
2023	—	`conf`	The Many Faces of Fairness: Exploring the Institutional Logics of Multistakeholder Microlending Recommendation. FAccT Jessie J. Smith, Anas Buhayh, Anushka Kathait, Pradeep Ragothaman, Nicholas Mattei, Robin Burke, Amy Voida
2022	—	`conf`	5th Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2022). UMAP (Adjunct Publication) Styliani Kleanthous, Bamshad Mobasher, Tsvika Kuflik, Bettina Berendt, Robin Burke, Jahna Otterbacher, Nasim Sonboli, Avital Shulner-Tal
2022	J	`jnl`	A Graph-Based Approach for Mitigating Multi-Sided Exposure Bias in Recommender Systems. ACM Trans. Inf. Syst. Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2022	A	`conf`	FAccTRec 2022: The 5th Workshop on Responsible Recommendation. RecSys Nasim Sonboli, Toshihiro Kamishima, Amifa Raj, Luca Belli, Robin Burke
2022	J	`jnl`	Fairness in Information Access Systems. Found. Trends Inf. Retr. Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz
2022	—	`ch.`	Fairness in Recommender Systems. Recommender Systems Handbook Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz
2022	—	`conf`	Multi-agent Social Choice for Dynamic Fairness-aware Recommendation. UMAP (Adjunct Publication) Robin Burke, Nicholas Mattei, Vladislav Grozin, Amy Voida, Nasim Sonboli
2022	—	`ch.`	Multistakeholder Recommender Systems. Recommender Systems Handbook Himan Abdollahpouri, Robin Burke
2022	—	`ch.`	Personalization, Fairness, and Post-Userism. Perspectives on Digital Humanism Robin Burke
2022	J	`jnl`	Personalized recommendation of PoIs to people with autism: technical perspective. Commun. ACM Robin Burke
2022	A	`conf`	Recommender Systems and Algorithmic Hate. RecSys Jessie J. Smith, Lucia Jayne, Robin Burke
2022	J	`jnl`	Recommender Systems and Algorithmic Hate. CoRR Jessie J. Smith, Lucia Jayne, Robin Burke
2022	J	`jnl`	The Multisided Complexity of Fairness in Recommender Systems. AI Mag. Nasim Sonboli, Robin Burke, Michael D. Ekstrand, Rishabh Mehrotra
2022	J	`jnl`	Who Pays? Personalization, Bossiness and the Cost of Fairness. CoRR Paresha Farastu, Nicholas Mattei, Robin Burke
2021	J	`jnl`	A Graph-based Approach for Mitigating Multi-sided Exposure Bias in Recommender Systems. CoRR Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2021	—	`conf`	Fair Candidate Ranking with Spatial Partitioning: Lessons from the SIOP ML competition. HR@RecSys Ian Burke, Robin Burke, Goran Kuljanin
2021	J	`jnl`	Fairness and Discrimination in Information Access Systems. CoRR Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz
2021	A	`conf`	Fairness and Transparency in Recommendation: The Users' Perspective. UMAP Nasim Sonboli, Jessie J. Smith, Florencia Cabral Berenfus, Robin Burke, Casey Fiesler
2021	J	`jnl`	Fairness and Transparency in Recommendation: The Users' Perspective. CoRR Nasim Sonboli, Jessie J. Smith, Florencia Cabral Berenfus, Robin Burke, Casey Fiesler
2021	J	`jnl`	Flatter Is Better: Percentile Transformations for Recommender Systems. ACM Trans. Intell. Syst. Technol. Masoud Mansoury, Robin Burke, Bamshad Mobasher
2021	J	`jnl`	Preface to the special issue on fair, accountable, and transparent recommender systems. User Model. User Adapt. Interact. Robin Burke, Michael D. Ekstrand, Nava Tintarev, Julita Vassileva
2021	A	`conf`	SimuRec: Workshop on Synthetic Data and Simulation Methods for Recommender Systems Research. RecSys Michael D. Ekstrand, Allison Chaney, Pablo Castells, Robin Burke, David Rohde, Manel Slokom
2021	—	`conf`	Towards an Experimental News User Community as Infrastructure for Recommendation Research (abstract). INRA@RecSys Joseph A. Konstan, Robin Burke, Edward C. Malthouse
2021	J	`jnl`	Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation. CoRR Masoud Mansoury, Himan Abdollahpouri, Bamshad Mobasher, Mykola Pechenizkiy, Robin Burke, Milad Sabouri
2021	J	`jnl`	User Factor Adaptation for User Embedding via Multitask Learning. CoRR Xiaolei Huang, Michael J. Paul, Robin Burke, Franck Dernoncourt, Mark Dredze
2021	A	`conf`	User-centered Evaluation of Popularity Bias in Recommender Systems. UMAP Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher, Edward C. Malthouse
2021	J	`jnl`	User-centered Evaluation of Popularity Bias in Recommender Systems. CoRR Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher, Edward C. Malthouse
2021	J	`jnl`	Virtual ACM UMAP 2020: the 28th conference on user modeling, adaptation, and personalization. SIGWEB Newsl. Robin Burke, Cristina Gena, Tsvi Kuflik, Ilaria Torre
2021	A	`conf`	librec-auto: A Tool for Recommender Systems Experimentation. CIKM Nasim Sonboli, Masoud Mansoury, Ziyue Guo, Shreyas Kadekodi, Weiwen Liu, Zijun Liu, Andrew Schwartz, Robin Burke
2020	J	`jnl`	"And the Winner Is...": Dynamic Lotteries for Multi-group Fairness-Aware Recommendation. CoRR Nasim Sonboli, Robin Burke, Nicholas Mattei, Farzad Eskandanian, Tian Gao
2020	J	`jnl`	Addressing the Multistakeholder Impact of Popularity Bias in Recommendation Through Calibration. CoRR Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher
2020	—	`ed.`	Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2020, Genoa, Italy, July 12-18, 2020 UMAP (Adjunct Publication) Tsvi Kuflik, Ilaria Torre, Robin Burke, Cristina Gena
2020	—	`conf`	Calibration in Collaborative Filtering Recommender Systems: a User-Centered Analysis. HT Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke
2020	J	`jnl`	Developing a Recommendation Benchmark for MLPerf Training and Inference. CoRR Carole-Jean Wu, Robin Burke, Ed H. Chi, Joseph A. Konstan, Julian J. McAuley, Yves Raimond, Hao Zhang
2020	J	`jnl`	Exploring User Opinions of Fairness in Recommender Systems. CoRR Jessie Smith, Nasim Sonboli, Casey Fiesler, Robin Burke
2020	A	`conf`	FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. UMAP Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2020	J	`jnl`	FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. CoRR Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2020	A	`conf`	Fairness-aware Recommendation with librec-auto. RecSys Nasim Sonboli, Robin Burke, Zijun Liu, Masoud Mansoury
2020	A	`conf`	Feedback Loop and Bias Amplification in Recommender Systems. CIKM Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2020	J	`jnl`	Feedback Loop and Bias Amplification in Recommender Systems. CoRR Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2020	J	`jnl`	Multistakeholder recommendation: Survey and research directions. User Model. User Adapt. Interact. Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Augusto Pizzato
2020	A	`conf`	Opportunistic Multi-aspect Fairness through Personalized Re-ranking. UMAP Nasim Sonboli, Farzad Eskandanian, Robin Burke, Weiwen Liu, Bamshad Mobasher
2020	J	`jnl`	Opportunistic Multi-aspect Fairness through Personalized Re-ranking. CoRR Nasim Sonboli, Farzad Eskandanian, Robin Burke, Weiwen Liu, Bamshad Mobasher
2020	A	`ed.`	Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2020, Genoa, Italy, July 12-18, 2020 UMAP Tsvi Kuflik, Ilaria Torre, Robin Burke, Cristina Gena
2020	J	`jnl`	Reading Chicago Reading: Quantitative Analysis of a Repeating Literary Program. Digit. Humanit. Q. John Shanahan, Robin Burke, Ana Lucic
2020	A	`conf`	The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation. RecSys Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher
2020	J	`jnl`	The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation. CoRR Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher
2020	J	`jnl`	Unfair Exposure of Artists in Music Recommendation. CoRR Himan Abdollahpouri, Robin Burke, Masoud Mansoury
2020	—	`conf`	Using Social Tag Embedding in a Collaborative Filtering Approach for Recommender Systems. WI/IAT Diego Sánchez-Moreno, María N. Moreno García, Nasim Sonboli, Bamshad Mobasher, Robin Burke
2019	—	`conf`	A Multistakeholder Recommender Systems Algorithm for Allocating Sponsored Recommendations. RMSE@RecSys Edward C. Malthouse, Khadija Ali Vakeel, Yasaman Kamyab Hessary, Robin Burke, Morana Fuduric
2019	—	`conf`	Algorithm Selection with Librec-auto. AMIR@ECIR Masoud Mansoury, Robin Burke
2019	J	`jnl`	Beyond Personalization: Research Directions in Multistakeholder Recommendation. CoRR Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Augusto Pizzato
2019	—	`conf`	Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. RMSE@RecSys Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy
2019	J	`jnl`	Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. CoRR Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy
2019	—	`conf`	Crank up the Volume: Preference Bias Amplification in Collaborative Recommendation. RMSE@RecSys Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke
2019	J	`jnl`	Crank up the volume: preference bias amplification in collaborative recommendation. CoRR Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke
2019	—	`conf`	FairUMAP 2019 Chairs' Welcome Overview. UMAP (Adjunct Publication) Bettina Berendt, Veronika Bogina, Robin Burke, Michael D. Ekstrand, Alan Hartman, Styliani Kleanthous, Tsvi Kuflik, Bamshad Mobasher, Jahna Otterbacher
2019	A*	`conf`	Fairness and Discrimination in Retrieval and Recommendation. SIGIR Michael D. Ekstrand, Robin Burke, Fernando Diaz
2019	A	`conf`	Fairness and discrimination in recommendation and retrieval. RecSys Michael D. Ekstrand, Robin Burke, Fernando Diaz
2019	J	`jnl`	Flatter is better: Percentile Transformations for Recommender Systems. CoRR Masoud Mansoury, Robin Burke, Bamshad Mobasher
2019	—	`conf`	Localized Fairness in Recommender Systems. UMAP (Adjunct Publication) Nasim Sonboli, Robin Burke
2019	Misc	`conf`	Managing Popularity Bias in Recommender Systems with Personalized Re-Ranking. FLAIRS Himan Abdollahpouri, Robin Burke, Bamshad Mobasher
2019	J	`jnl`	Managing Popularity Bias in Recommender Systems with Personalized Re-ranking. CoRR Himan Abdollahpouri, Robin Burke, Bamshad Mobasher
2019	—	`conf`	Multi-stakeholder Recommendation and its Connection to Multi-sided Fairness. RMSE@RecSys Himan Abdollahpouri, Robin Burke
2019	J	`jnl`	Multi-stakeholder Recommendation and its Connection to Multi-sided Fairness. CoRR Himan Abdollahpouri, Robin Burke
2019	A	`conf`	Personalized fairness-aware re-ranking for microlending. RecSys Weiwen Liu, Jun Guo, Nasim Sonboli, Robin Burke, Shengyu Zhang
2019	—	`ed.`	Proceedings of the Workshop on Recommendation in Multi-stakeholder Environments co-located with the 13th ACM Conference on Recommender Systems (RecSys 2019), Copenhagen, Denmark, September 20, 2019. RMSE@RecSys Robin Burke, Himan Abdollahpouri, Edward C. Malthouse, K. P. Thai, Yongfeng Zhang
2019	—	`conf`	RMSE: Workshop on Recommendation in Multi-stakeholder Environments. RMSE@RecSys Robin Burke, Himan Abdollahpouri, Edward C. Malthouse, K. P. Thai, Yongfeng Zhang
2019	A	`conf`	Recommendation in multistakeholder environments. RecSys Robin Burke, Himan Abdollahpouri, Edward C. Malthouse, K. P. Thai, Yongfeng Zhang
2019	J	`jnl`	Reducing Popularity Bias in Recommendation Over Time. CoRR Himan Abdollahpouri, Robin Burke
2019	J	`jnl`	Research Commentary on Recommendations with Side Information: A Survey and Research Directions. CoRR Zhu Sun, Qing Guo, Jie Yang, Hui Fang, Guibing Guo, Jie Zhang, Robin Burke
2019	J	`jnl`	Research commentary on recommendations with side information: A survey and research directions. Electron. Commer. Res. Appl. Zhu Sun, Qing Guo, Jie Yang, Hui Fang, Guibing Guo, Jie Zhang, Robin Burke
2019	J	`jnl`	The Impact of Popularity Bias on Fairness and Calibration in Recommendation. CoRR Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher
2019	—	`conf`	The Unfairness of Popularity Bias in Recommendation. RMSE@RecSys Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher
2019	J	`jnl`	The Unfairness of Popularity Bias in Recommendation. CoRR Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher
2019	—	`conf`	Unsupervised Clustering with Smoothing for Detecting Paratext Boundaries in Scanned Documents. JCDL Ana Lucic, Robin Burke, John Shanahan
2018	A	`conf`	Automating recommender systems experimentation with librec-auto. RecSys Masoud Mansoury, Robin Burke, Aldo Ordonez-Gauger, Xavier Sepulveda
2018	—	`conf`	Balanced Neighborhoods for Multi-sided Fairness in Recommendation. FAT Robin Burke, Nasim Sonboli, Aldo Ordonez-Gauger
2018	Misc	`conf`	Inferring User Expertise from Social Tagging in Music Recommender Systems for Streaming Services. HAIS Diego Sánchez-Moreno, María N. Moreno García, Nasim Sonboli, Bamshad Mobasher, Robin Burke
2018	A	`conf`	Multistakeholder recommendation with provider constraints. RecSys Özge Sürer, Robin Burke, Edward C. Malthouse
2018	J	`jnl`	Personalizing Fairness-aware Re-ranking. CoRR Weiwen Liu, Robin Burke
2018	—	`ch.`	Recommender Systems Based on Social Networks. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. Fatemeh Vahedian, Robin Burke
2018	J	`jnl`	Synthetic Attribute Data for Evaluating Consumer-side Fairness. CoRR Robin Burke, Jackson Kontny, Nasim Sonboli
2018	—	`conf`	UMAP 2018 Fairness in User Modeling, Adaptation and Personalization (FairUMAP 2018) Chairs' Welcome & Organization: Preface. UMAP (Adjunct Publication) Bamshad Mobasher, Robin Burke, Michael D. Ekstrand, Bettina Berendt
2018	J	`jnl`	Value-Aware Item Weighting for Long-Tail Recommendation. CoRR Himan Abdollahpouri, Robin Burke, Bamshad Mobasher
2017	A	`conf`	A Clustering Approach for Personalizing Diversity in Collaborative Recommender Systems. UMAP Farzad Eskandanian, Bamshad Mobasher, Robin Burke
2017	—	`conf`	Circulation Modeling of Library Book Promotions. JCDL Robin Burke, Ana Lucic, John Shanahan
2017	A	`conf`	Controlling Popularity Bias in Learning-to-Rank Recommendation. RecSys Himan Abdollahpouri, Robin Burke, Bamshad Mobasher
2017	—	`ch.`	Emotions in Context-Aware Recommender Systems. Emotions and Personality in Personalized Services Yong Zheng, Bamshad Mobasher, Robin Burke
2017	J	`jnl`	Multirelational Recommendation in Heterogeneous Networks. ACM Trans. Web Fatemeh Vahedian, Robin Burke, Bamshad Mobasher
2017	J	`jnl`	Multisided Fairness for Recommendation. CoRR Robin Burke
2017	J	`jnl`	Patterns of Multistakeholder Recommendation. CoRR Robin Burke, Himan Abdollahpouri
2017	A	`conf`	Recommender Systems as Multistakeholder Environments. UMAP Himan Abdollahpouri, Robin Burke, Bamshad Mobasher
2017	—	`conf`	Using Uncertain Graphs to Automatically Generate Event Flows from News Stories. HT (Extended Proceedings) Laura Christiansen, Bamshad Mobasher, Robin Burke
2017	A	`conf`	VAMS 2017: Workshop on Value-Aware and Multistakeholder Recommendation. RecSys Robin Burke, Gediminas Adomavicius, Ido Guy, Jan Krasnodebski, Luiz Augusto Pizzato, Yi Zhang, Himan Abdollahpouri
2016	A	`conf`	User-Oriented Context Suggestion. UMAP Yong Zheng, Bamshad Mobasher, Robin Burke
2015	A*	`conf`	Adapting to User Preference Changes in Interactive Recommendation. IJCAI Negar Hariri, Bamshad Mobasher, Robin Burke
2015	—	`ch.`	Robust Collaborative Recommendation. Recommender Systems Handbook Robin Burke, Michael P. O'Mahony, Neil J. Hurley
2013	—	`conf`	Supporting therapists in motion-based gaming for brain injury rehabilitation. CHI Extended Abstracts Cynthia Putnam, Jinghui Cheng, Doris C. Rusch, André Berthiaume, Robin Burke
2011	—	`conf`	Context-Aware Recommendation Based On Review Mining. ITWP@IJCAI Negar Hariri, Bamshad Mobasher, Robin Burke, Yong Zheng
2011	—	`conf`	Experience Discovery: hybrid recommendation of student activities using social network data. HetRec@RecSys Robin Burke, Yong Zheng, Scott Riley
2010	—	`conf`	Improving the effectiveness of collaborative recommendation with ontology-based user profiles. HetRec@RecSys Ahu Sieg, Bamshad Mobasher, Robin Burke
2010	—	`conf`	Ontology-Based Collaborative Recommendation. ITWP@UMAP Ahu Sieg, Bamshad Mobasher, Robin Burke
2007	—	`conf`	Game Design as a Writing Course in the Liberal Arts. FECS Amber Settle, Robin Burke, Lucia Dettori