| Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions G Adomavicius, A Tuzhilin IEEE transactions on knowledge and data engineering 17 (6), 734-749, 2005 | 14955 | 2005 |
| Context-aware recommender systems G Adomavicius, A Tuzhilin Recommender systems handbook, 217-253, 2011 | 3281 | 2011 |
| Incorporating contextual information in recommender systems using a multidimensional approach G Adomavicius, R Sankaranarayanan, S Sen, A Tuzhilin ACM Transactions on Information systems (TOIS) 23 (1), 103-145, 2005 | 1769 | 2005 |
| Improving aggregate recommendation diversity using ranking-based techniques G Adomavicius, YO Kwon IEEE Transactions on Knowledge and Data Engineering 24 (5), 896-911, 2011 | 883 | 2011 |
| System and method for dynamic profiling of users in one-to-one applications and for validating user rules AS Tuzhilin, G Adomavicius US Patent 7,603,331, 2009 | 784* | 2009 |
| New recommendation techniques for multicriteria rating systems G Adomavicius, YO Kwon IEEE Intelligent Systems 22 (3), 48-55, 2007 | 708 | 2007 |
| Architectures, systems, apparatus, methods, and computer-readable medium for providing recommendations to users and applications using multidimensional data A Tuzhilin, G Adomavicius US Patent 8,103,611, 2012 | 634 | 2012 |
| Personalization technologies: a process-oriented perspective G Adomavicius, A Tuzhilin Communications of the ACM 48 (10), 83-90, 2005 | 596 | 2005 |
| Multi-criteria recommender systems G Adomavicius, N Manouselis, YO Kwon Recommender systems handbook, 769-803, 2010 | 454 | 2010 |
| Using data mining methods to build customer profiles G Adomavicius, A Tuzhilin Computer 34 (2), 74-82, 2001 | 442 | 2001 |
| Making sense of technology trends in the information technology landscape: A design science approach G Adomavicius, JC Bockstedt, A Gupta, RJ Kauffman Mis Quarterly, 779-809, 2008 | 371 | 2008 |
| A parallel multilevel method for adaptively refined Cartesian grids with embedded boundaries M Aftosmis, M Berger, G Adomavicius 38th Aerospace Sciences Meeting and Exhibit, 808, 2000 | 310 | 2000 |
| Do recommender systems manipulate consumer preferences? A study of anchoring effects G Adomavicius, JC Bockstedt, SP Curley, J Zhang Information Systems Research 24 (4), 956-975, 2013 | 302 | 2013 |
| Multistakeholder recommendation: Survey and research directions H Abdollahpouri, G Adomavicius, R Burke, I Guy, D Jannach, ... User Modeling and User-Adapted Interaction 30, 127-158, 2020 | 289 | 2020 |
| Expert-driven validation of rule-based user models in personalization applications G Adomavicius, A Tuzhilin Data Mining and Knowledge Discovery 5, 33-58, 2001 | 271 | 2001 |
| Understanding user-generated content and customer engagement on Facebook business pages M Yang, Y Ren, G Adomavicius Information Systems Research 30 (3), 839-855, 2019 | 232 | 2019 |
| User profiling in personalization applications through rule discovery and validation G Adomavicius, A Tuzhilin Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999 | 228 | 1999 |
| Technology roles and paths of influence in an ecosystem model of technology evolution G Adomavicius, JC Bockstedt, A Gupta, RJ Kauffman Information Technology and Management 8, 185-202, 2007 | 217 | 2007 |
| Recommendations with a purpose D Jannach, G Adomavicius Proceedings of the 10th ACM conference on recommender systems, 7-10, 2016 | 203 | 2016 |
| Impact of data characteristics on recommender systems performance G Adomavicius, J Zhang ACM Transactions on Management Information Systems (TMIS) 3 (1), 1-17, 2012 | 199 | 2012 |
