Collaborative filtering recommender systems MD Ekstrand, JT Riedl, JA Konstan Foundations and Trends® in Human–Computer Interaction 4 (2), 81-173, 2011 | 1662 | 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 | 272 | 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 | 263 | 2018 |
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 | 246 | 2011 |
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 | 178 | 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 | 169 | 2020 |
Fairness in information access systems MD Ekstrand, A Das, R Burke, F Diaz Foundations and Trends® in Information Retrieval 16 (1-2), 1-177, 2022 | 144* | 2022 |
Rating-based collaborative filtering: algorithms and evaluation D Kluver, MD Ekstrand, JA Konstan Social information access: Systems and technologies, 344-390, 2018 | 140 | 2018 |
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 | 136 | 2015 |
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 | 131 | 2016 |
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 | 123 | 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 | 116 | 2015 |
Privacy for all: Ensuring fair and equitable privacy protections MD Ekstrand, R Joshaghani, H Mehrpouyan Conference on fairness, accountability and transparency, 35-47, 2018 | 96 | 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 | 86 | 2012 |
Lenskit for Python: Next-generation software for recommender systems experiments MD Ekstrand Proceedings of the 29th ACM international conference on information …, 2020 | 82 | 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 | 59 | 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 | 56 | 2011 |
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 | 50 | 2019 |
Measuring fairness in ranked results: An analytical and empirical comparison A Raj, MD Ekstrand Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 48 | 2022 |
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 | 48 | 2012 |