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Gediminas Adomavicius
Gediminas Adomavicius
Professor of Information and Decision Sciences, University of Minnesota
Verified email at umn.edu
Title
Cited by
Cited by
Year
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
147592005
Context-aware recommender systems
G Adomavicius, A Tuzhilin
Recommender systems handbook, 217-253, 2011
32252011
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
17522005
Improving aggregate recommendation diversity using ranking-based techniques
G Adomavicius, YO Kwon
IEEE Transactions on Knowledge and Data Engineering 24 (5), 896-911, 2011
8612011
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
773*2009
New recommendation techniques for multicriteria rating systems
G Adomavicius, YO Kwon
IEEE Intelligent Systems 22 (3), 48-55, 2007
7042007
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
6252012
Personalization technologies: a process-oriented perspective
G Adomavicius, A Tuzhilin
Communications of the ACM 48 (10), 83-90, 2005
5882005
Multi-criteria recommender systems
G Adomavicius, N Manouselis, YO Kwon
Recommender systems handbook, 769-803, 2010
4542010
Using data mining methods to build customer profiles
G Adomavicius, A Tuzhilin
Computer 34 (2), 74-82, 2001
4322001
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
3562008
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
3052000
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
2862013
Expert-driven validation of rule-based user models in personalization applications
G Adomavicius, A Tuzhilin
Data Mining and Knowledge Discovery 5, 33-58, 2001
2722001
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
2702020
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
2251999
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
2172019
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
2122007
Recommendations with a purpose
D Jannach, G Adomavicius
Proceedings of the 10th ACM conference on recommender systems, 7-10, 2016
1932016
Impact of data characteristics on recommender systems performance
G Adomavicius, J Zhang
ACM Transactions on Management Information Systems (TMIS) 3 (1), 1-17, 2012
1852012
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