| Unifying collaborative and content-based filtering J Basilico, T Hofmann Proceedings of the twenty-first international conference on Machine learning, 9, 2004 | 560 | 2004 |
| Netflix recommendations: Beyond the 5 stars (part 1) X Amatriain, J Basilico Netflix Tech Blog 6, 2012 | 226 | 2012 |
| Recommender systems in industry: A netflix case study X Amatriain, J Basilico Recommender systems handbook, 385-419, 2015 | 161 | 2015 |
| Deep learning for recommender systems: A Netflix case study H Steck, L Baltrunas, E Elahi, D Liang, Y Raimond, J Basilico AI Magazine 42 (3), 7-18, 2021 | 149 | 2021 |
| Past, present, and future of recommender systems: An industry perspective X Amatriain, J Basilico Proceedings of the 10th ACM conference on recommender systems, 211-214, 2016 | 93 | 2016 |
| Artwork personalization at Netflix A Chandrashekar, F Amat, J Basilico, T Jebara Netflix technology blog 7, 2017 | 85 | 2017 |
| A joint framework for collaborative and content filtering J Basilico, T Hofmann Proceedings of the 27th annual international ACM SIGIR conference on …, 2004 | 70 | 2004 |
| Artwork personalization at Netflix F Amat, A Chandrashekar, T Jebara, J Basilico Proceedings of the 12th ACM conference on recommender systems, 487-488, 2018 | 67 | 2018 |
| Comet: A recipe for learning and using large ensembles on massive data JD Basilico, MA Munson, TG Kolda, KR Dixon, WP Kegelmeyer 2011 IEEE 11th international conference on data mining, 41-50, 2011 | 51 | 2011 |
| Learning a personalized homepage C Alvino, J Basilico The Netflix Tech Blog 9, 2015 | 38 | 2015 |
| Using navigation to improve recommendations in real-time CY Wu, CV Alvino, AJ Smola, J Basilico Proceedings of the 10th ACM Conference on Recommender Systems, 341-348, 2016 | 35 | 2016 |
| Deepqa jeopardy! gamification: a machine-learning perspective AK Baughman, W Chuang, KR Dixon, Z Benz, J Basilico IEEE transactions on computational intelligence and AI in games 6 (1), 55-66, 2013 | 31 | 2013 |
| Accordion: a trainable simulator for long-term interactive systems J McInerney, E Elahi, J Basilico, Y Raimond, T Jebara Proceedings of the 15th ACM Conference on Recommender Systems, 102-113, 2021 | 24 | 2021 |
| System architectures for personalization and recommendation X Amatriain, J Basilico the Netflix Techblog: http://techblog. netflix. com/2013/03 …, 2013 | 23 | 2013 |
| Recommending for the world Y Raimond, J Basilico Netflix tech blog 17, 2016 | 20 | 2016 |
| Media content rankings for discovery of novel content JD Basilico US Patent 9,430,532, 2016 | 17 | 2016 |
| Improved team performance using EEG-and context-based cognitive-state classifications for a vehicle crew KR Dixon, K Hagemann, J Basilico, C Forsythe, S Rothe, M Schrauf, ... Foundations of Augmented Cognition. Neuroergonomics and Operational …, 2009 | 16 | 2009 |
| Déja vu: The importance of time and causality in recommender systems J Basilico, Y Raimond Proceedings of the eleventh ACM conference on recommender systems, 342-342, 2017 | 15 | 2017 |
| Recent trends in personalization: a Netflix perspective J Basilico ICML 2019 Workshop on Adaptive and Multitask Learning. ICML, 2019 | 13 | 2019 |
| Performance assessment to enhance training effectiveness SM Stevens-Adams, JD Basilico, RG Abbott, CJ Gieseler, C Forsythe Proceedings of the Interservice/Industry Training, Simulation, and Education …, 2010 | 13 | 2010 |
