| Collaborative filtering recommender systems MD Ekstrand, JT Riedl, JA Konstan Foundations and Trends in Human-Computer Interaction 4 (2), 81-173, 2011 | 1360 | 2011 |
| Rethinking the recommender research ecosystem: reproducibility, openness, and LensKit MD Ekstrand, M Ludwig, JA Konstan, JT Riedl Proceedings of the fifth ACM conference on Recommender systems, 133-140, 2011 | 209 | 2011 |
| User perception of differences in recommender algorithms MD Ekstrand, FM Harper, MC Willemsen, JA Konstan Proceedings of the 8th ACM Conference on Recommender systems, 161-168, 2014 | 197 | 2014 |
| All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness MD Ekstrand, M Tian, IM Azpiazu, JD Ekstrand, O Anuyah, D McNeill, ... Conference on Fairness, Accountability and Transparency, 172-186, 2018 | 119 | 2018 |
| Automatically building research reading lists MD Ekstrand, P Kannan, JA Stemper, JT Butler, JA Konstan, JT Riedl Proceedings of the fourth ACM conference on Recommender systems, 159-166, 2010 | 110 | 2010 |
| Teaching recommender systems at large scale: evaluation and lessons learned from a hybrid MOOC JA Konstan, JD Walker, DC Brooks, K Brown, MD Ekstrand ACM Transactions on Computer-Human Interaction (TOCHI) 22 (2), 1-23, 2015 | 103 | 2015 |
| Letting users choose recommender algorithms: An experimental study MD Ekstrand, D Kluver, FM Harper, JA Konstan Proceedings of the 9th ACM Conference on Recommender Systems, 11-18, 2015 | 98 | 2015 |
| Rating-based collaborative filtering: algorithms and evaluation D Kluver, MD Ekstrand, JA Konstan Social Information Access, 344-390, 2018 | 91 | 2018 |
| Exploring author gender in book rating and recommendation MD Ekstrand, M Tian, MRI Kazi, H Mehrpouyan, D Kluver Proceedings of the 12th ACM Conference on Recommender Systems, 242-250, 2018 | 88 | 2018 |
| When recommenders fail: predicting recommender failure for algorithm selection and combination M Ekstrand, J Riedl Proceedings of the sixth ACM conference on Recommender systems, 233-236, 2012 | 70 | 2012 |
| Behaviorism is not enough: Better recommendations through listening to users MD Ekstrand, MC Willemsen Proceedings of the 10th ACM Conference on Recommender Systems, 221-224, 2016 | 68 | 2016 |
| Privacy for All: Ensuring Fair and Equitable Privacy Protections MD Ekstrand, R Joshaghani, H Mehrpouyan Conference on Fairness, Accountability and Transparency, 35-47, 2018 | 60 | 2018 |
| Evaluating stochastic rankings with expected exposure F Diaz, B Mitra, MD Ekstrand, AJ Biega, B Carterette Proceedings of the 29th ACM International Conference on Information …, 2020 | 58 | 2020 |
| Rating support interfaces to improve user experience and recommender accuracy TT Nguyen, D Kluver, TY Wang, PM Hui, MD Ekstrand, MC Willemsen, ... Proceedings of the 7th ACM conference on Recommender systems, 149-156, 2013 | 53 | 2013 |
| Searching for software learning resources using application context M Ekstrand, W Li, T Grossman, J Matejka, G Fitzmaurice Proceedings of the 24th annual ACM symposium on User interface software and …, 2011 | 49 | 2011 |
| LensKit for Python: Next-Generation Software for Recommender Systems Experiments MD Ekstrand Proceedings of the 29th ACM International Conference on Information …, 2020 | 42* | 2020 |
| How many bits per rating? D Kluver, TT Nguyen, M Ekstrand, S Sen, J Riedl Proceedings of the sixth ACM conference on Recommender systems, 99-106, 2012 | 42 | 2012 |
| LensKit: a modular recommender framework MD Ekstrand, M Ludwig, J Kolb, JT Riedl Proceedings of the fifth ACM conference on Recommender systems, 349-350, 2011 | 40 | 2011 |
| rv you're dumb: identifying discarded work in Wiki article history MD Ekstrand, JT Riedl Proceedings of the 5th international Symposium on Wikis and Open …, 2009 | 35 | 2009 |
| Fairness and Discrimination in Retrieval and Recommendation MD Ekstrand, R Burke, F Diaz Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 28 | 2019 |
Joseph A. KonstanUniversity of MinnesotaVerified email at umn.edu
