Robin D. Burke

According to our database, Robin D. Burke authored at least 184 papers between 1994 and 2024.

Collaborative distances:

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

2024

RecSOI: recommending research directions using statements of ignorance.

Adrien Bibal, Nourah M. Salem, Rémi Cardon, Elizabeth K. White, Daniel E. Acuna, Robin Burke, Lawrence E. Hunter

J. Biomed. Semant., December, 2024

Post-Userist Recommender Systems : A Manifesto.

Robin Burke, Morgan Sylvester

CoRR, 2024

Data Generation via Latent Factor Simulation for Fairness-aware Re-ranking.

Elena Stefancova, Cassidy All, Joshua Paup, Martin Homola, Nicholas Mattei, Robin Burke

CoRR, 2024

Conducting Recommender Systems User Studies Using POPROX.

Robin Burke, Joseph A. Konstan, Michael D. Ekstrand

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

Social Choice for Heterogeneous Fairness in Recommendation.

Amanda Aird, Elena Stefancova, Cassidy All, Amy Voida, Martin Homola, Nicholas Mattei, Robin Burke

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

Comparative Explanations for Recommendation: Research Directions.

Meysam Varasteh, Elizabeth McKinnie, Amanda Aird, Daniel E. Acuña, Robin Burke

Proceedings of the 11th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with 18th ACM Conference on Recommender Systems (RecSys 2024), 2024

Recommend Me? Designing Fairness Metrics with Providers.

Jessie J. Smith, Aishwarya Satwani, Robin Burke, Casey Fiesler

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023

Exploring Social Choice Mechanisms for Recommendation Fairness in SCRUF.

Amanda Aird, Cassidy All, Paresha Farastu, Elena Stefancova, Joshua Sun, Nicholas Mattei, Robin Burke

CoRR, 2023

Dynamic fairness-aware recommendation through multi-agent social choice.

Amanda Aird, Paresha Farastu, Joshua Sun, Amy Voida, Nicholas Mattei, Robin Burke

CoRR, 2023

6th Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2023).

Bamshad Mobasher, Styliani Kleanthous, Jahna Otterbacher, Robin Burke, Avital Shulner-Tal

Proceedings of the Adjunct Proceedings of the 31st ACM Conference on User Modeling, 2023

"It's just a robot that looks at numbers": Restoring Journalistic Voice in News Recommendation.

Nihal Alaqabawy, Aishwarya Satwani, Amy Voida, Robin Burke

Proceedings of the International Workshop on News Recommendation and Analytics co-located with the 2023 ACM Conference on Recommender Systems (RecSys 2023), 2023

The Many Faces of Fairness: Exploring the Institutional Logics of Multistakeholder Microlending Recommendation.

Jessie J. Smith, Anas Buhayh, Anushka Kathait, Pradeep Ragothaman, Nicholas Mattei, Robin Burke, Amy Voida

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Fairness in Recommender Systems.

Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz

Proceedings of the Recommender Systems Handbook, 2022

Multistakeholder Recommender Systems.

Himan Abdollahpouri, Robin Burke

Proceedings of the Recommender Systems Handbook, 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

Fairness in Information Access Systems.

Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz

Found. Trends Inf. Retr., 2022

Who Pays? Personalization, Bossiness and the Cost of Fairness.

Paresha Farastu, Nicholas Mattei, Robin Burke

CoRR, 2022

Personalized recommendation of PoIs to people with autism: technical perspective.

Robin Burke

Commun. ACM, 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

Recommender Systems and Algorithmic Hate.

Jessie J. Smith, Lucia Jayne, Robin Burke

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

Personalization, Fairness, and Post-Userism.

Robin Burke

Perspectives on Digital Humanism, 2022

2021

Preface to the special issue on fair, accountable, and transparent recommender systems.

Robin Burke, Michael D. Ekstrand, Nava Tintarev, Julita Vassileva

User Model. User Adapt. Interact., 2021

Flatter Is Better: Percentile Transformations for Recommender Systems.

Masoud Mansoury, Robin Burke, Bamshad Mobasher

ACM Trans. Intell. Syst. Technol., 2021

Virtual ACM UMAP 2020: the 28th conference on user modeling, adaptation, and personalization.

Robin Burke, Cristina Gena, Tsvi Kuflik, Ilaria Torre

SIGWEB Newsl., 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 and Discrimination in Information Access Systems.

Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz

CoRR, 2021

User Factor Adaptation for User Embedding via Multitask Learning.

Xiaolei Huang, Michael J. Paul, Robin Burke, Franck Dernoncourt, Mark Dredze

CoRR, 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

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

Towards an Experimental News User Community as Infrastructure for Recommendation Research (abstract).

Joseph A. Konstan, Robin Burke, Edward C. Malthouse

Proceedings of the 9th International Workshop on News Recommendation and Analytics (INRA 2021) co-located with 15th ACM Conference on Recommender Systems (RecSys 2021), 2021

SimuRec: Workshop on Synthetic Data and Simulation Methods for Recommender Systems Research.

Michael D. Ekstrand, Allison Chaney, Pablo Castells, Robin Burke, David Rohde, Manel Slokom

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Fair Candidate Ranking with Spatial Partitioning: Lessons from the SIOP ML competition.

Ian Burke, Robin Burke, Goran Kuljanin

Proceedings of the Workshop on Recommender Systems for Human Resources (RecSys in HR 2021) co-located with the 15th ACM Conference on Recommender Systems (RecSys 2021), Amsterdam, The Netherlands, 27th September, 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

Multistakeholder recommendation: Survey and research directions.

Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Augusto Pizzato

User Model. User Adapt. Interact., 2020

Reading Chicago Reading: Quantitative Analysis of a Repeating Literary Program.

John Shanahan, Robin Burke, Ana Lucic

Digit. Humanit. Q., 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

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

Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher

CoRR, 2020

Unfair Exposure of Artists in Music Recommendation.

Himan Abdollahpouri, Robin Burke, Masoud Mansoury

CoRR, 2020

Developing a Recommendation Benchmark for MLPerf Training and Inference.

Carole-Jean Wu, Robin Burke, Ed H. Chi, Joseph A. Konstan, Julian J. McAuley, Yves Raimond, Hao Zhang

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

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

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

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

Research commentary on recommendations with side information: A survey and research directions.

Zhu Sun, Qing Guo, Jie Yang, Hui Fang, Guibing Guo, Jie Zhang, Robin Burke

Electron. Commer. Res. Appl., 2019

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

Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher

CoRR, 2019

Reducing Popularity Bias in Recommendation Over Time.

Himan Abdollahpouri, Robin Burke

CoRR, 2019

Beyond Personalization: Research Directions in Multistakeholder Recommendation.

Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Augusto Pizzato

CoRR, 2019

Localized Fairness in Recommender Systems.

Nasim Sonboli, Robin Burke

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

FairUMAP 2019 Chairs' Welcome Overview.

Bettina Berendt, Veronika Bogina, Robin Burke, Michael D. Ekstrand, Alan Hartman, Styliani Kleanthous, Tsvi Kuflik, Bamshad Mobasher, Jahna Otterbacher

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

Fairness and Discrimination in Retrieval and Recommendation.

Michael D. Ekstrand, Robin Burke, Fernando Diaz

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 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

A Multistakeholder Recommender Systems Algorithm for Allocating Sponsored Recommendations.

Edward C. Malthouse, Khadija Ali Vakeel, Yasaman Kamyab Hessary, Robin Burke, Morana Fuduric

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

Fairness and discrimination in recommendation and retrieval.

Michael D. Ekstrand, Robin Burke, Fernando Diaz

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

RMSE: Workshop on Recommendation in Multi-stakeholder Environments.

Robin Burke, Himan Abdollahpouri, Edward C. Malthouse, K. P. Thai, Yongfeng Zhang

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

Recommendation in multistakeholder environments.

Robin Burke, Himan Abdollahpouri, Edward C. Malthouse, K. P. Thai, Yongfeng Zhang

Proceedings of the 13th ACM Conference on Recommender Systems, 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

Multi-stakeholder Recommendation and its Connection to Multi-sided Fairness.

Himan Abdollahpouri, 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

Unsupervised Clustering with Smoothing for Detecting Paratext Boundaries in Scanned Documents.

Ana Lucic, Robin Burke, John Shanahan

Proceedings of the 19th ACM/IEEE Joint Conference on Digital Libraries, 2019

Managing Popularity Bias in Recommender Systems with Personalized Re-Ranking.

Himan Abdollahpouri, Robin Burke, Bamshad Mobasher

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

Recommender Systems Based on Social Networks.

Fatemeh Vahedian, Robin Burke

Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

Synthetic Attribute Data for Evaluating Consumer-side Fairness.

Robin Burke, Jackson Kontny, Nasim Sonboli

CoRR, 2018

Personalizing Fairness-aware Re-ranking.

Weiwen Liu, Robin Burke

CoRR, 2018

Value-Aware Item Weighting for Long-Tail Recommendation.

Himan Abdollahpouri, Robin Burke, Bamshad Mobasher

CoRR, 2018

UMAP 2018 Fairness in User Modeling, Adaptation and Personalization (FairUMAP 2018) Chairs' Welcome & Organization: Preface.

Bamshad Mobasher, Robin Burke, Michael D. Ekstrand, Bettina Berendt

Proceedings of the Adjunct Publication of the 26th Conference on User Modeling, 2018

Multistakeholder recommendation with provider constraints.

Özge Sürer, Robin Burke, Edward C. Malthouse

Proceedings of the 12th ACM Conference on Recommender Systems, 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

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

2017

Emotions in Context-Aware Recommender Systems.

Yong Zheng, Bamshad Mobasher, Robin Burke

Proceedings of the Emotions and Personality in Personalized Services, 2017

Multirelational Recommendation in Heterogeneous Networks.

Fatemeh Vahedian, Robin Burke, Bamshad Mobasher

ACM Trans. Web, 2017

Patterns of Multistakeholder Recommendation.

Robin Burke, Himan Abdollahpouri

CoRR, 2017

Multisided Fairness for Recommendation.

Robin Burke

CoRR, 2017

Weighted Random Walk Sampling for Multi-Relational Recommendation.

Fatemeh Vahedian, Robin D. Burke, Bamshad Mobasher

Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 2017

A Clustering Approach for Personalizing Diversity in Collaborative Recommender Systems.

Farzad Eskandanian, Bamshad Mobasher, Robin Burke

Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 2017

Recommender Systems as Multistakeholder Environments.

Himan Abdollahpouri, Robin Burke, Bamshad Mobasher

Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 2017

VAMS 2017: Workshop on Value-Aware and Multistakeholder Recommendation.

Robin Burke, Gediminas Adomavicius, Ido Guy, Jan Krasnodebski, Luiz Augusto Pizzato, Yi Zhang, Himan Abdollahpouri

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

Controlling Popularity Bias in Learning-to-Rank Recommendation.

Himan Abdollahpouri, Robin Burke, Bamshad Mobasher

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

Circulation Modeling of Library Book Promotions.

Robin Burke, Ana Lucic, John Shanahan

Proceedings of the 2017 ACM/IEEE Joint Conference on Digital Libraries, 2017

Using Uncertain Graphs to Automatically Generate Event Flows from News Stories.

Laura Christiansen, Bamshad Mobasher, Robin Burke

Proceedings of the Workshops Proceedings and Tutorials of the 28th ACM Conference on Hypertext and Social Media (HT 2017), 2017

2016

Collaborative Recommendation of Informal Learning Experiences.

Robin D. Burke, Farzad Eskandanian

Proceedings of the 2016 IEEE/WIC/ACM International Conference on Web Intelligence, 2016

Educational Recommendation with Multiple Stakeholders.

Robin D. Burke, Himan Abdollahpouri

Proceedings of the 2016 IEEE/WIC/ACM International Conference on Web Intelligence, 2016

User-Oriented Context Suggestion.

Yong Zheng, Bamshad Mobasher, Robin Burke

Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization, 2016

Towards Multi-Stakeholder Utility Evaluation of Recommender Systems.

Robin D. Burke, Himan Abdollahpouri, Bamshad Mobasher, Trinadh Gupta

Proceedings of the Late-breaking Results, 2016

Weighted Random Walks for Meta-Path Expansion in Heterogeneous Networks.

Fatemeh Vahedian, Robin D. Burke, Bamshad Mobasher

Proceedings of the Poster Track of the 10th ACM Conference on Recommender Systems (RecSys 2016), 2016

User Segmentation for Controlling Recommendation Diversity.

Farzad Eskandanian, Bamshad Mobasher, Robin D. Burke

Proceedings of the Poster Track of the 10th ACM Conference on Recommender Systems (RecSys 2016), 2016

Meta-Path Selection for Extended Multi-Relational Matrix Factorization.

Fatemeh Vahedian, Robin D. Burke, Bamshad Mobasher

Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, 2016

2015

Robust Collaborative Recommendation.

Robin Burke, Michael P. O'Mahony, Neil J. Hurley

Proceedings of the Recommender Systems Handbook, 2015

Similarity-Based Context-Aware Recommendation.

Yong Zheng, Bamshad Mobasher, Robin D. Burke

Proceedings of the Web Information Systems Engineering - WISE 2015, 2015

Integrating Context Similarity with Sparse Linear Recommendation Model.

Yong Zheng, Bamshad Mobasher, Robin D. Burke

Proceedings of the User Modeling, Adaptation and Personalization, 2015

Network-Based Extension of Multi-Relational Factorization Models.

Fatemeh Vahedian, Robin D. Burke, Bamshad Mobasher

Proceedings of the Poster Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Adapting Recommendations to Contextual Changes Using Hierarchical Hidden Markov Models.

Mehdi Hosseinzadeh Aghdam, Negar Hariri, Bamshad Mobasher, Robin D. Burke

Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Incorporating Context Correlation into Context-aware Matrix Factorization.

Yong Zheng, Bamshad Mobasher, Robin D. Burke

Proceedings of the IJCAI 2015 Joint Workshop on Constraints and Preferences for Configuration and Recommendation and Intelligent Techniques for Web Personalization co-located with the 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), 2015

Adapting to User Preference Changes in Interactive Recommendation.

Negar Hariri, Bamshad Mobasher, Robin Burke

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

CARSKit: A Java-Based Context-Aware Recommendation Engine.

Yong Zheng, Bamshad Mobasher, Robin D. Burke

Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

2014

Context Recommendation Using Multi-label Classification.

Yong Zheng, Bamshad Mobasher, Robin D. Burke

Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, August 11-14, 2014, 2014

User Partitioning Hybrid for Tag Recommendation.

Jonathan Gemmell, Bamshad Mobasher, Robin D. Burke

Proceedings of the User Modeling, Adaptation, and Personalization, 2014

Hybrid Recommendation in Heterogeneous Networks.

Robin D. Burke, Fatemeh Vahedian, Bamshad Mobasher

Proceedings of the User Modeling, Adaptation, and Personalization, 2014

Splitting approaches for context-aware recommendation: an empirical study.

Yong Zheng, Robin D. Burke, Bamshad Mobasher

Proceedings of the Symposium on Applied Computing, 2014

CSLIM: contextual SLIM recommendation algorithms.

Yong Zheng, Bamshad Mobasher, Robin D. Burke

Proceedings of the Eighth ACM Conference on Recommender Systems, 2014

Predicting Component Utilities for Linear-Weighted Hybrid Recommendation.

Fatemeh Vahedian, Robin D. Burke

Proceedings of the 6th Workshop on Recommender Systems and the Social Web (RSWeb 2014) co-located with the 8th ACM Conference on Recommender Systems (RecSys 2014), 2014

Context adaptation in interactive recommender systems.

Negar Hariri, Bamshad Mobasher, Robin D. Burke

Proceedings of the Eighth ACM Conference on Recommender Systems, 2014

Resource Recommendation in Social Annotation Systems Based on User Partitioning.

Jonathan Gemmell, Bamshad Mobasher, Robin D. Burke

Proceedings of the E-Commerce and Web Technologies - 15th International Conference, 2014

Deviation-Based Contextual SLIM Recommenders.

Yong Zheng, Bamshad Mobasher, Robin D. Burke

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

2013

Recommendation with Differential Context Weighting.

Yong Zheng, Robin D. Burke, Bamshad Mobasher

Proceedings of the User Modeling, Adaptation, and Personalization, 2013

The Role of Emotions in Context-aware Recommendation.

Yong Zheng, Bamshad Mobasher, Robin D. Burke

Proceedings of the 3rd Workshop on Human Decision Making in Recommender Systems in conjunction with the 7th ACM Conference on Recommender Systems (RecSys 2013), 2013

Query-driven context aware recommendation.

Negar Hariri, Bamshad Mobasher, Robin D. Burke

Proceedings of the Seventh ACM Conference on Recommender Systems, 2013

Social Web Recommendation using Metapaths.

Robin D. Burke, Fatemeh Vahedian

Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), 2013

Supporting therapists in motion-based gaming for brain injury rehabilitation.

Cynthia Putnam, Jinghui Cheng, Doris C. Rusch, André Berthiaume, Robin Burke

Proceedings of the 2013 ACM SIGCHI Conference on Human Factors in Computing Systems, 2013

2012

Preface to the special issue on user interfaces for recommender systems.

Alexander Felfernig, Robin D. Burke, Pearl Pu

User Model. User Adapt. Interact., 2012

Resource recommendation in social annotation systems: A linear-weighted hybrid approach.

Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin D. Burke

J. Comput. Syst. Sci., 2012

<i>Recommender Systems: An Introduction</i>, by Dietmar Jannach, Markus Zanker, Alexander Felfernig, and Gerhard FriedrichCambridge University Press, 2011, 336 pages. ISBN: 978-0-521-49336-9.

Robin Burke

Int. J. Hum. Comput. Interact., 2012

Using social tags to infer context in hybrid music recommendation.

Negar Hariri, Bamshad Mobasher, Robin D. Burke

Proceedings of the Twelfth International Workshop on Web Information and Data Management, 2012

Modeling topic trends on the social web using temporal signatures.

Laura Christiansen, Thomas Schimoler, Robin D. Burke, Bamshad Mobasher

Proceedings of the Twelfth International Workshop on Web Information and Data Management, 2012

Context-aware music recommendation based on latenttopic sequential patterns.

Negar Hariri, Bamshad Mobasher, Robin D. Burke

Proceedings of the Sixth ACM Conference on Recommender Systems, 2012

Differential Context Relaxation for Context-Aware Travel Recommendation.

Yong Zheng, Robin D. Burke, Bamshad Mobasher

Proceedings of the E-Commerce and Web Technologies - 13th International Conference, 2012

2011

Matching Recommendation Technologies and Domains.

Robin D. Burke, Maryam Ramezani

Proceedings of the Recommender Systems Handbook, 2011

Robust Collaborative Recommendation.

Robin D. Burke, Michael P. O'Mahony, Neil J. Hurley

Proceedings of the Recommender Systems Handbook, 2011

Recommendation in the Social Web.

Robin D. Burke, Jonathan Gemmell, Andreas Hotho, Robert Jäschke

AI Mag., 2011

Recommender Systems: An Overview.

Robin D. Burke, Alexander Felfernig, Mehmet H. Göker

AI Mag., 2011

Tag-Based Resource Recommendation in Social Annotation Applications.

Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin D. Burke

Proceedings of the User Modeling, Adaption and Personalization, 2011

Interactive multi-party critiquing for group recommendation.

Francesca Guzzi, Francesco Ricci, Robin D. Burke

Proceedings of the 2011 ACM Conference on Recommender Systems, 2011

Experience Discovery: hybrid recommendation of student activities using social network data.

Robin Burke, Yong Zheng, Scott Riley

Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, 2011

Context-Aware Recommendation Based On Review Mining.

Negar Hariri, Bamshad Mobasher, Robin Burke, Yong Zheng

Proceedings of the 9th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems, 2011

Recommendation by Example in Social Annotation Systems.

Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin D. Burke

Proceedings of the E-Commerce and Web Technologies - 12th International Conference, 2011

2010

Ontology-Based Collaborative Recommendation.

Ahu Sieg, Bamshad Mobasher, Robin Burke

Proceedings of the 8th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems, 2010

Improving the effectiveness of collaborative recommendation with ontology-based user profiles.

Ahu Sieg, Bamshad Mobasher, Robin Burke

Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems, 2010

Evaluating the dynamic properties of recommendation algorithms.

Robin D. Burke

Proceedings of the 2010 ACM Conference on Recommender Systems, 2010

Resource Recommendation in Collaborative Tagging Applications.

Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin D. Burke

Proceedings of the E-Commerce and Web Technologies, 11th International Conference, 2010

Hybrid tag recommendation for social annotation systems.

Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin D. Burke

Proceedings of the 19th ACM Conference on Information and Knowledge Management, 2010

2009

Evaluating the Impact of Attacks in Collaborative Tagging Environments.

Maryam Ramezani, Jeff J. Sandvig, Thomas Schimoler, Jonathan Gemmell, Bamshad Mobasher, Robin D. Burke

Proceedings of the 12th IEEE International Conference on Computational Science and Engineering, 2009

2008

A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms.

Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke

IEEE Data Eng. Bull., 2008

Personalized recommendation in social tagging systems using hierarchical clustering.

Andriy Shepitsen, Jonathan Gemmell, Bamshad Mobasher, Robin D. Burke

Proceedings of the 2008 ACM Conference on Recommender Systems, 2008

Robust recommender systems.

Robin D. Burke

Proceedings of the 2008 ACM Conference on Recommender Systems, 2008

Personalizing Navigation in Folksonomies Using Hierarchical Tag Clustering.

Jonathan Gemmell, Andriy Shepitsen, Bamshad Mobasher, Robin D. Burke

Proceedings of the Data Warehousing and Knowledge Discovery, 10th International Conference, 2008

Constraint-based recommender systems: technologies and research issues.

Alexander Felfernig, Robin D. Burke

Proceedings of the 10th International Conference on Electronic Commerce 2008, 2008

2007

Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness.

Bamshad Mobasher, Robin D. Burke, Runa Bhaumik, Chad Williams

ACM Trans. Internet Techn., 2007

Defending recommender systems: detection of profile injection attacks.

Chad Williams, Bamshad Mobasher, Robin D. Burke

Serv. Oriented Comput. Appl., 2007

Attacks and Remedies in Collaborative Recommendation.

Bamshad Mobasher, Robin D. Burke, Runa Bhaumik, Jeff J. Sandvig

IEEE Intell. Syst., 2007

Learning Ontology-Based User Profiles: A Semantic Approach to Personalized Web Search.

Ahu Sieg, Bamshad Mobasher, Robin D. Burke

IEEE Intell. Informatics Bull., 2007

Robustness of collaborative recommendation based on association rule mining.

Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke

Proceedings of the 2007 ACM Conference on Recommender Systems, 2007

Ontological User Profiles for Representing Context in Web Search.

Ahu Sieg, Bamshad Mobasher, Robin D. Burke

Proceedings of the 2007 IEEE/WIC/ACM International Conference on Web Intelligence and International Conference on Intelligent Agent Technology, 2007

Game Design as a Writing Course in the Liberal Arts.

Amber Settle, Robin Burke, Lucia Dettori

Proceedings of the 2007 International Conference on Frontiers in Education: Computer Science & Computer Engineering, 2007

Impact of Relevance Measures on the Robustness and Accuracy of Collaborative Filtering.

Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke

Proceedings of the E-Commerce and Web Technologies, 8th International Conference, 2007

Crawling Attacks Against Web-based Recommender Systems.

Runa Bhaumik, Robin D. Burke, Bamshad Mobasher

Proceedings of the 2007 International Conference on Data Mining, 2007

Representing Context in Web Search with Ontological User Profiles.

Ahu Sieg, Bamshad Mobasher, Robin D. Burke

Proceedings of the Modeling and Using Context, 2007

Web search personalization with ontological user profiles.

Ahu Sieg, Bamshad Mobasher, Robin D. Burke

Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management, 2007

Hybrid Web Recommender Systems.

Robin D. Burke

Proceedings of the Adaptive Web, Methods and Strategies of Web Personalization, 2007

2006

The Sixth International Conference on Case-based Reasoning.

Hector Muñoz-Avila, Francesco Ricci, Robin D. Burke

AI Mag., 2006

Detecting Profile Injection Attacks in Collaborative Recommender Systems.

Robin D. Burke, Bamshad Mobasher, Chad Williams, Runa Bhaumik

Proceedings of the Eighth IEEE International Conference on E-Commerce Technology (CEC 2006) / Third IEEE International Conference on Enterprise Computing, 2006

Detecting Profile Injection Attacks in Collaborative Filtering: A Classification-Based Approach.

Chad Williams, Bamshad Mobasher, Robin D. Burke, Runa Bhaumik

Proceedings of the Advances in Web Mining and Web Usage Analysis, 2006

Classification features for attack detection in collaborative recommender systems.

Robin D. Burke, Bamshad Mobasher, Chad Williams, Runa Bhaumik

Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

Model-Based Collaborative Filtering as a Defense against Profile Injection Attacks.

Bamshad Mobasher, Robin D. Burke, Jeff J. Sandvig

Proceedings of the Proceedings, 2006

2005

Analysis and Detection of Segment-Focused Attacks Against Collaborative Recommendation.

Bamshad Mobasher, Robin D. Burke, Chad Williams, Runa Bhaumik

Proceedings of the Advances in Web Mining and Web Usage Analysis, 2005

Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems.

Robin D. Burke, Bamshad Mobasher, Runa Bhaumik, Chad Williams

Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

2004

Hybrid Recommender Systems with Case-Based Components.

Robin D. Burke

Proceedings of the Advances in Case-Based Reasoning, 7th European Conference, 2004

2003

Hybrid Systems for Personalized Recommendations.

Robin D. Burke

Proceedings of the Intelligent Techniques for Web Personalization, IJCAI 2003 Workshop, 2003

Concept Based Query Enhancement in the ARCH Search Agent.

Ahu Sieg, Bamshad Mobasher, Steven L. Lytinen, Robin D. Burke

Proceedings of the International Conference on Internet Computing, 2003

2002

Hybrid Recommender Systems: Survey and Experiments.

Robin D. Burke

User Model. User Adapt. Interact., 2002

Interactive Critiquing for Catalog Navigation in E-Commerce.

Robin D. Burke

Artif. Intell. Rev., 2002

2001

Salticus: guided crawling for personal digital libraries.

Robin D. Burke

Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, 2001

Ranking Algorithms for Costly Similarity Measures.

Robin D. Burke

Proceedings of the Case-Based Reasoning Research and Development, 2001

2000

Entree Chicago Recommendation Data.

Robin Burke

Dataset, March, 2000

A Case-Based Reasoning Approach to Collaborative Filtering.

Robin D. Burke

Proceedings of the Advances in Case-Based Reasoning, 5th European Workshop, 2000

1999

The Wasabi Personal Shopper: A Case-Based Recommender System.

Robin D. Burke

Proceedings of the Sixteenth National Conference on Artificial Intelligence and Eleventh Conference on Innovative Applications of Artificial Intelligence, 1999

1998

Answering Questions for an Organization Online.

Vladimir A. Kulyukin, Kristian J. Hammond, Robin D. Burke

Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

1997

The FindMe Approach to Assisted Browsing.

Robin D. Burke, Kristian J. Hammond, Benjamin C. Young

IEEE Expert, 1997

Question Answering from Frequently Asked Question Files: Experiences with the FAQ FINDER System.

Robin D. Burke, Kristian J. Hammond, Vladimir A. Kulyukin, Steven L. Lytinen, Noriko Tomuro, Scott Schoenberg

AI Mag., 1997

1996

Conceptual indexing and active retrieval of video for interactive learning environments.

Robin D. Burke

Knowl. Based Syst., 1996

Case-Based Teaching of Cardiac Auscultation.

Kurt D. Fenstermacher, Robin D. Burke, Kristian J. Hammond

Proceedings of the Learning for the Real World: Proceedings of the Second International Conference on the Learning Sciences, 1996

Knowledge-Based Navigation of Complex Information Spaces.

Robin D. Burke, Kristian J. Hammond, Benjamin C. Young

Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

1995

A Case-Based Approach to Knowledge Navigation.

Kristian J. Hammond, Robin D. Burke, Steven L. Lytinen

Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

1994

A Case-Based Approach to Knowledge Navigation.

Kristian J. Hammond, Robin D. Burke, Kathryn Schmitt

Proceedings of the Knowledge Discovery in Databases: Papers from the 1994 AAAI Workshop, 1994

Tailoring Retrieval to Support Case-Based Teaching.

Robin D. Burke, Alex Kass

Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, WA, USA, July 31, 1994