Michael D. Ekstrand

118 papers A* 7A 32B 4Misc 2Journal 52Unranked 19
YearRankTypeTitle / Venue / Authors
2026 J jnl
Recall, Robustness, and Lexicographic Evaluation.
Trans. Recomm. Syst.
Fernando Diaz, Michael D. Ekstrand, Bhaskar Mitra
2025 — conf
Conducting Recommender Systems User Studies Using POPROX.
UMAP (Adjunct Publication)
Robin Burke, Michael D. Ekstrand
2025 A conf
FAccTRec 2025: The 8th Workshop on Responsible Recommendation.
RecSys
Michael D. Ekstrand, Toshihiro Kamishima, Amifa Raj, Karlijn Dinnissen
2025 — conf
Fairness in Information Access Conceptual Foundations and New Directions.
ECIR (5)
Michael D. Ekstrand
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 J jnl
Report from the 4th Strategic Workshop on Information Retrieval in Lorne (SWIRL 2025).
SIGIR Forum
Johanne R. Trippas, J. Shane Culpepper, Mohammad Aliannejadi, James Allan, Enrique Amigó, Jaime Arguello, Leif Azzopardi, Peter Bailey, Jamie Callan, Rob Capra, Nick Craswell, W. Bruce Croft, Jeff Dalton, Gianluca Demartini, Laura Dietz, Zhicheng Dou, Carsten Eickhoff, Michael D. Ekstrand, Nicola Ferro, Norbert Fuhr, Dorota Glowacka, Faegheh Hasibi, Danula Hettiachchi, Rosie Jones, Jaap Kamps, Noriko Kando, Sarvnaz Karimi, Makoto P. Kato, Bevan Koopman, Yiqun Liu, Chenglong Ma, Joel Mackenzie, Maria Maistro, Jiaxin Mao, Dana McKay, Bhaskar Mitra, Stefano Mizzaro, Alistair Moffat, Josiane Mothe, Iadh Ounis, Lida Rashidi, Yongli Ren, Mark Sanderson, Rodrygo L. T. Santos, Falk Scholer, Chirag Shah, Laurianne Sitbon, Ian Soboroff, Damiano Spina, Paul Thomas, Julián Urbano, Arjen P. de Vries, Ryen White, Abby Yuan, Hamed Zamani, Oleg Zendel, Min Zhang, Shengyao Zhuang, Justin Zobel, Guido Zuccon
2025 J jnl
Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor.
CoRR
Alexandra Olteanu, Su Lin Blodgett, Agathe Balayn, Angelina Wang, Fernando Diaz, Flávio du Pin Calmon, Margaret Mitchell, Michael D. Ekstrand, Reuben Binns, Solon Barocas
2025 — conf
The Evolving Landscape of Youth Online Safety: Insights from News Media Analysis.
WebSci
Mohammad Namvarpour, Elham Aghakhani, Michael D. Ekstrand, Rezvaneh Rezapour, Afsaneh Razi
2025 — conf
The Impossibility of Fair LLMs.
ACL (1)
Jacy Reese Anthis, Kristian Lum, Michael D. Ekstrand, Avi Feller, Chenhao Tan
2025 — conf
User and Recommender Behavior Over Time: Contextualizing Activity Effectiveness Diversity and Fairness in Book Recommendation.
UMAP (Adjunct Publication)
Samira Vaez Barenji, Sushobhan Parajuli, Michael D. Ekstrand
2025 J jnl
User and Recommender Behavior Over Time: Contextualizing Activity, Effectiveness, Diversity, and Fairness in Book Recommendation.
CoRR
Samira Vaez Barenji, Sushobhan Parajuli, Michael D. Ekstrand
2025 J jnl
We're Still Doing It (All) Wrong: Recommender Systems, Fifteen Years Later.
CoRR
Alan Said, Maria Soledad Pera, Michael D. Ekstrand
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 A conf
AltRecSys: A Workshop on Alternative, Unexpected, and Critical Ideas in Recommendation.
RecSys
Michael D. Ekstrand, Maria Soledad Pera, Alan Said
2024 J jnl
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis.
Trans. Recomm. Syst.
Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Chloé Bakalar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy Xian Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan
2024 A conf
Conducting Recommender Systems User Studies Using POPROX.
RecSys
Robin Burke, Joseph A. Konstan, Michael D. Ekstrand
2024 J jnl
Distributionally-Informed Recommender System Evaluation.
Trans. Recomm. Syst.
Michael D. Ekstrand, Ben Carterette, Fernando Diaz
2024 A conf
FAccTRec 2024: The 7th Workshop on Responsible Recommendation.
RecSys
Michael D. Ekstrand, Toshihiro Kamishima, Amifa Raj, Karlijn Dinnissen
2024 A conf
It's Not You, It's Me: The Impact of Choice Models and Ranking Strategies on Gender Imbalance in Music Recommendation.
RecSys
Andres Ferraro, Michael D. Ekstrand, Christine Bauer
2024 J jnl
It's Not You, It's Me: The Impact of Choice Models and Ranking Strategies on Gender Imbalance in Music Recommendation.
CoRR
Andres Ferraro, Michael D. Ekstrand, Christine Bauer
2024 — conf
Multiple Testing for IR and Recommendation System Experiments.
ECIR (3)
Ngozi Ihemelandu, Michael D. Ekstrand
2024 — conf
Not Just Algorithms: Strategically Addressing Consumer Impacts in Information Retrieval.
ECIR (4)
Michael D. Ekstrand, Lex Beattie, Maria Soledad Pera, Henriette Cramer
2024 J jnl
The Impossibility of Fair LLMs.
CoRR
Jacy Reese Anthis, Kristian Lum, Michael D. Ekstrand, Avi Feller, Alexander D'Amour, Chenhao Tan
2024 — conf
Towards Optimizing Ranking in Grid-Layout for Provider-Side Fairness.
ECIR (5)
Amifa Raj, Michael D. Ekstrand
2023 — conf
Candidate Set Sampling for Evaluating Top-N Recommendation.
WI/IAT
Ngozi Ihemelandu, Michael D. Ekstrand
2023 J jnl
Candidate Set Sampling for Evaluating Top-N Recommendation.
CoRR
Ngozi Ihemelandu, Michael D. Ekstrand
2023 J jnl
Distributionally-Informed Recommender System Evaluation.
CoRR
Michael D. Ekstrand, Ben Carterette, Fernando Diaz
2023 A conf
FAccTRec 2023: The 6th Workshop on Responsible Recommendation.
RecSys
Michael D. Ekstrand, Jean Garcia-Gathright, Nasim Sonboli, Amifa Raj, Karlijn Dinnissen
2023 J jnl
Inference at Scale Significance Testing for Large Search and Recommendation Experiments.
CoRR
Ngozi Ihemelandu, Michael D. Ekstrand
2023 A* conf
Inference at Scale: Significance Testing for Large Search and Recommendation Experiments.
SIGIR
Ngozi Ihemelandu, Michael D. Ekstrand
2023 A conf
Introducing LensKit-Auto, an Experimental Automated Recommender System (AutoRecSys) Toolkit.
RecSys
Tobias Vente, Michael D. Ekstrand, Joeran Beel
2023 B conf
Much Ado About Gender: Current Practices and Future Recommendations for Appropriate Gender-Aware Information Access.
CHIIR
Christine Pinney, Amifa Raj, Alex Hanna, Michael D. Ekstrand
2023 J jnl
Much Ado About Gender: Current Practices and Future Recommendations for Appropriate Gender-Aware Information Access.
CoRR
Christine Pinney, Amifa Raj, Alex Hanna, Michael D. Ekstrand
2023 J jnl
Overview of the TREC 2021 Fair Ranking Track.
CoRR
Michael D. Ekstrand, Graham McDonald, Amifa Raj, Isaac L. Johnson
2023 J jnl
Overview of the TREC 2022 Fair Ranking Track.
CoRR
Michael D. Ekstrand, Graham McDonald, Amifa Raj, Isaac Johnson
2023 A* conf
Patterns of Gender-Specializing Query Reformulation.
SIGIR
Amifa Raj, Bhaskar Mitra, Nick Craswell, Michael D. Ekstrand
2023 J jnl
Patterns of gender-specializing query reformulation.
CoRR
Amifa Raj, Bhaskar Mitra, Nick Craswell, Michael D. Ekstrand
2023 J jnl
Responsible AI Research Needs Impact Statements Too.
CoRR
Alexandra Olteanu, Michael D. Ekstrand, Carlos Castillo, Jina Suh
2023 J jnl
Seeking Information with a More Knowledgeable Other.
Interactions
Michael D. Ekstrand, Maria Soledad Pera, Katherine Landau Wright
2023 J jnl
Towards Measuring Fairness in Grid Layout in Recommender Systems.
CoRR
Amifa Raj, Michael D. Ekstrand
2023 J jnl
Unified Browsing Models for Linear and Grid Layouts.
CoRR
Amifa Raj, Michael D. Ekstrand
2022 J jnl
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis.
CoRR
Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy X. Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan
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 J jnl
Fire Dragon and Unicorn Princess; Gender Stereotypes and Children's Products in Search Engine Responses.
CoRR
Amifa Raj, Michael D. Ekstrand
2022 J jnl
Matching Consumer Fairness Objectives & Strategies for RecSys.
CoRR
Michael D. Ekstrand, Maria Soledad Pera
2022 A* conf
Measuring Fairness in Ranked Results: An Analytical and Empirical Comparison.
SIGIR
Amifa Raj, Michael D. Ekstrand
2022 — conf
Overview of the TREC 2022 Fair Ranking Track.
TREC
Michael D. Ekstrand, Graham McDonald, Amifa Raj, Isaac Johnson
2022 A ed.
RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18 - 23, 2022
RecSys
Jennifer Golbeck, F. Maxwell Harper, Vanessa Murdock, Michael D. Ekstrand, Bracha Shapira, Justin Basilico, Keld T. Lundgaard, Even Oldridge
2022 J jnl
The Multisided Complexity of Fairness in Recommender Systems.
AI Mag.
Nasim Sonboli, Robin Burke, Michael D. Ekstrand, Rishabh Mehrotra
2021 A conf
Baby Shark to Barracuda: Analyzing Children's Music Listening Behavior.
RecSys
Lawrence Spear, Ashlee Milton, Garrett Allen, Amifa Raj, Michael Green, Michael D. Ekstrand, Maria Soledad Pera
2021 A* conf
Estimation of Fair Ranking Metrics with Incomplete Judgments.
WWW
Ömer Kirnap, Fernando Diaz, Asia Biega, Michael D. Ekstrand, Ben Carterette, Emine Yilmaz
2021 J jnl
Estimation of Fair Ranking Metrics with Incomplete Judgments.
CoRR
Ömer Kirnap, Fernando Diaz, Asia Biega, Michael D. Ekstrand, Ben Carterette, Emine Yilmaz
2021 J jnl
Exploring author gender in book rating and recommendation.
User Model. User Adapt. Interact.
Michael D. Ekstrand, Daniel Kluver
2021 A conf
FAccTRec 2021: The 4th Workshop on Responsible Recommendation.
RecSys
Michael D. Ekstrand, Pierre-Nicolas Schwab, Toshihiro Kamishima, Nasim Sonboli
2021 J jnl
Fairness and Discrimination in Information Access Systems.
CoRR
Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz
2021 J jnl
Multiversal Simulacra: Understanding Hypotheticals and Possible Worlds Through Simulation.
CoRR
Michael D. Ekstrand
2021 J jnl
Overview of the TREC 2020 Fair Ranking Track.
CoRR
Asia J. Biega, Fernando Diaz, Michael D. Ekstrand, Sergey Feldman, Sebastian Kohlmeier
2021 — conf
Overview of the TREC 2021 Fair Ranking Track.
TREC
Michael D. Ekstrand, Amifa Raj, Graham McDonald, Isaac Johnson
2021 J jnl
Pink for Princesses, Blue for Superheroes: The Need to Examine Gender Stereotypes in Kid's Products in Search and Recommendations.
CoRR
Amifa Raj, Ashlee Milton, Michael D. Ekstrand
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
Privacy as a Planned Behavior: Effects of Situational Factors on Privacy Perceptions and Plans.
UMAP
A. K. M. Nuhil Mehdy, Michael D. Ekstrand, Bart P. Knijnenburg, Hoda Mehrpouyan
2021 J jnl
Privacy as a Planned Behavior: Effects of Situational Factors on Privacy Perceptions and Plans.
CoRR
A. K. M. Nuhil Mehdy, Michael D. Ekstrand, Bart P. Knijnenburg, Hoda Mehrpouyan
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
Statistical Inference: The Missing Piece of RecSys Experiment Reliability Discourse.
Perspectives@RecSys
Ngozi Ihemelandu, Michael D. Ekstrand
2021 J jnl
Statistical Inference: The Missing Piece of RecSys Experiment Reliability Discourse.
CoRR
Ngozi Ihemelandu, Michael D. Ekstrand
2020 A conf
3rd FAccTRec Workshop: Responsible Recommendation.
RecSys
Michael D. Ekstrand, Pierre-Nicolas Schwab, Jean Garcia-Gathright, Toshihiro Kamishima, Nasim Sonboli
2020 J jnl
Comparing Fair Ranking Metrics.
CoRR
Amifa Raj, Connor Wood, Ananda Montoly, Michael D. Ekstrand
2020 J jnl
Enhancing classroom instruction with online news.
Aslib J. Inf. Manag.
Michael D. Ekstrand, Katherine Landau Wright, Maria Soledad Pera
2020 B conf
Estimating Error and Bias in Offline Evaluation Results.
CHIIR
Mucun Tian, Michael D. Ekstrand
2020 J jnl
Estimating Error and Bias in Offline Evaluation Results.
CoRR
Mucun Tian, Michael D. Ekstrand
2020 A conf
Evaluating Stochastic Rankings with Expected Exposure.
CIKM
Fernando Diaz, Bhaskar Mitra, Michael D. Ekstrand, Asia J. Biega, Ben Carterette
2020 J jnl
Evaluating Stochastic Rankings with Expected Exposure.
CoRR
Fernando Diaz, Bhaskar Mitra, Michael D. Ekstrand, Asia J. Biega, Ben Carterette
2020 A conf
FairUMAP 2020: The 3rd Workshop on Fairness in User Modeling, Adaptation and Personalization.
UMAP
Bamshad Mobasher, Styliani Kleanthous, Michael D. Ekstrand, Bettina Berendt, Jahna Otterbacher, Avital Shulner-Tal
2020 A conf
LensKit for Python: Next-Generation Software for Recommender Systems Experiments.
CIKM
Michael D. Ekstrand
2020 J jnl
Overview of the TREC 2019 Fair Ranking Track.
CoRR
Asia J. Biega, Fernando Diaz, Michael D. Ekstrand, Sebastian Kohlmeier
2020 — conf
UMAP 2020 Fairness in User Modeling, Adaptation and Personalization (FairUMAP 2020) Chairs' Welcome.
UMAP (Adjunct Publication)
Bamshad Mobasher, Styliani Kleanthous, Bettina Berendt, Michael D. Ekstrand, Jahna Otterbacher, Avital Shulner-Tal
2019 J jnl
FACTS-IR: fairness, accountability, confidentiality, transparency, and safety in information retrieval.
SIGIR Forum
Alexandra Olteanu, Jean Garcia-Gathright, Maarten de Rijke, Michael D. Ekstrand, Adam Roegiest, Aldo Lipani, Alex Beutel, Ana Lucic, Ana-Andreea Stoica, Anubrata Das, Asia Biega, Bart Voorn, Claudia Hauff, Damiano Spina, David D. Lewis, Douglas W. Oard, Emine Yilmaz, Faegheh Hasibi, Gabriella Kazai, Graham McDonald, Hinda Haned, Iadh Ounis, Ilse van der Linden, Joris Baan, Kamuela N. Lau, Krisztian Balog, Mahmoud F. Sayed, Maria Panteli, Mark Sanderson, Matthew Lease, Preethi Lahoti, Toshihiro Kamishima
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
Proceedings of FACTS-IR 2019.
CoRR
Alexandra Olteanu, Jean Garcia-Gathright, Maarten de Rijke, Michael D. Ekstrand
2019 J jnl
Recommender Systems Notation: Proposed Common Notation for Teaching and Research.
CoRR
Michael D. Ekstrand, Joseph A. Konstan
2019 A conf
StoryTime: eliciting preferences from children for book recommendations.
RecSys
Ashlee Milton, Michael Green, Adam Keener, Joshua Ames, Michael D. Ekstrand, Maria Soledad Pera
2019 A* conf
Workshop on Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval (FACTS-IR).
SIGIR
Alexandra Olteanu, Jean Garcia-Gathright, Maarten de Rijke, Michael D. Ekstrand
2018 A conf
2nd FATREC workshop: responsible recommendation.
RecSys
Toshihiro Kamishima, Pierre-Nicolas Schwab, Michael D. Ekstrand
2018 — conf
All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness.
FAT
Michael D. Ekstrand, Mucun Tian, Ion Madrazo Azpiazu, Jennifer D. Ekstrand, Oghenemaro Anuyah, David McNeill, Maria Soledad Pera
2018 J jnl
Exploring Author Gender in Book Rating and Recommendation.
CoRR
Michael D. Ekstrand, Mucun Tian, Mohammed R. Imran Kazi, Hoda Mehrpouyan, Daniel Kluver
2018 A conf
Exploring author gender in book rating and recommendation.
RecSys
Michael D. Ekstrand, Mucun Tian, Mohammed R. Imran Kazi, Hoda Mehrpouyan, Daniel Kluver
2018 J jnl
From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing and Recommender Systems into Predictive Sciences (Dagstuhl Perspectives Workshop 17442).
Dagstuhl Manifestos
Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, Justin Zobel
2018 — conf
Privacy for All: Ensuring Fair and Equitable Privacy Protections.
FAT
Michael D. Ekstrand, Rezvan Joshaghani, Hoda Mehrpouyan
2018 A ed.
Proceedings of the 12th ACM Conference on Recommender Systems, RecSys 2018, Vancouver, BC, Canada, October 2-7, 2018
RecSys
Sole Pera, Michael D. Ekstrand, Xavier Amatriain, John O'Donovan
2018 — ch.
Rating-Based Collaborative Filtering: Algorithms and Evaluation.
Social Information Access
Daniel Kluver, Michael D. Ekstrand, Joseph A. Konstan
2018 J jnl
The Dagstuhl Perspectives Workshop on Performance Modeling and Prediction.
SIGIR Forum
Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, Justin Zobel
2018 J jnl
The LKPY Package for Recommender Systems Experiments: Next-Generation Tools and Lessons Learned from the LensKit Project.
CoRR
Michael D. Ekstrand
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
2017 A conf
FATREC Workshop on Responsible Recommendation.
RecSys
Michael D. Ekstrand, Amit Sharma
2017 Misc conf
Recommender Response to Diversity and Popularity Bias in User Profiles.
FLAIRS
Sushma Channamsetty, Michael D. Ekstrand
2017 Misc conf
Sturgeon and the Cool Kids: Problems with Random Decoys for Top-N Recommender Evaluation.
FLAIRS
Michael D. Ekstrand, Vaibhav Mahant
2017 — conf
The Demographics of Cool: Popularity and Recommender Performance for Different Groups of Users.
RecSys Posters
Michael D. Ekstrand, Maria Soledad Pera
2016 A conf
Behaviorism is Not Enough: Better Recommendations through Listening to Users.
RecSys
Michael D. Ekstrand, Martijn C. Willemsen
2016 J jnl
Dependency Injection with Static Analysis and Context-Aware Policy.
J. Object Technol.
Michael D. Ekstrand, Michael Ludwig
2015 A conf
Letting Users Choose Recommender Algorithms: An Experimental Study.
RecSys
Michael D. Ekstrand, Daniel Kluver, F. Maxwell Harper, Joseph A. Konstan
2015 J jnl
Teaching Recommender Systems at Large Scale: Evaluation and Lessons Learned from a Hybrid MOOC.
ACM Trans. Comput. Hum. Interact.
Joseph A. Konstan, J. D. Walker, D. Christopher Brooks, Keith Brown, Michael D. Ekstrand
2014 B conf
Teaching recommender systems at large scale: evaluation and lessons learned from a hybrid MOOC.
L@S
Joseph A. Konstan, J. D. Walker, D. Christopher Brooks, Keith Brown, Michael D. Ekstrand
2014 A conf
User perception of differences in recommender algorithms.
RecSys
Michael D. Ekstrand, F. Maxwell Harper, Martijn C. Willemsen, Joseph A. Konstan
2013 A conf
Rating support interfaces to improve user experience and recommender accuracy.
RecSys
Tien T. Nguyen, Daniel Kluver, Ting-Yu Wang, Pik-Mai Hui, Michael D. Ekstrand, Martijn C. Willemsen, John Riedl
2012 A conf
How many bits per rating?
RecSys
Daniel Kluver, Tien T. Nguyen, Michael D. Ekstrand, Shilad Sen, John Riedl
2012 B conf
RecStore: an extensible and adaptive framework for online recommender queries inside the database engine.
EDBT
Justin J. Levandoski, Mohamed Sarwat, Mohamed F. Mokbel, Michael D. Ekstrand
2012 A conf
When recommenders fail: predicting recommender failure for algorithm selection and combination.
RecSys
Michael D. Ekstrand, John Riedl
2011 J jnl
Collaborative Filtering Recommender Systems.
Found. Trends Hum. Comput. Interact.
Michael D. Ekstrand, John Riedl, Joseph A. Konstan
2011 A conf
LensKit: a modular recommender framework.
RecSys
Michael D. Ekstrand, Michael Ludwig, Jack Kolb, John Riedl
2011 J jnl
RecBench: Benchmarks for Evaluating Performance of Recommender System Architectures.
Proc. VLDB Endow.
Justin J. Levandoski, Michael D. Ekstrand, Michael Ludwig, Ahmed Eldawy, Mohamed F. Mokbel, John Riedl
2011 A conf
Rethinking the recommender research ecosystem: reproducibility, openness, and LensKit.
RecSys
Michael D. Ekstrand, Michael Ludwig, Joseph A. Konstan, John Riedl
2011 A* conf
Searching for software learning resources using application context.
UIST
Michael D. Ekstrand, Wei Li, Tovi Grossman, Justin Matejka, George W. Fitzmaurice
2011 A conf
UCERSTI 2: second workshop on user-centric evaluation of recommender systems and their interfaces.
RecSys
Martijn C. Willemsen, Dirk G. F. M. Bollen, Michael D. Ekstrand
2010 A conf
Automatically building research reading lists.
RecSys
Michael D. Ekstrand, Praveen Kannan, James A. Stemper, John T. Butler, Joseph A. Konstan, John Riedl
2009 — conf
rv you're dumb: identifying discarded work in Wiki article history.
Int. Sym. Wikis
Michael D. Ekstrand, John Riedl