Gediminas Adomavicius
Gediminas Adomavicius
Professor of Information and Decision Sciences, University of Minnesota
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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
Context-Aware Recommender Systems
G Adomavicius, B Mobasher, F Ricci, A Tuzhilin
AI Magazine 32 (3), 67-80, 2011
Context-aware recommender systems
G Adomavicius, A Tuzhilin
Recommender systems handbook, 217-253, 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
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
Improving aggregate recommendation diversity using ranking-based techniques
G Adomavicius, YO Kwon
IEEE Transactions on Knowledge and Data Engineering 24 (5), 896-911, 2011
New recommendation techniques for multicriteria rating systems
G Adomavicius, YO Kwon
IEEE Intelligent Systems 22 (3), 48-55, 2007
Personalization technologies: a process-oriented perspective
G Adomavicius, A Tuzhilin
Communications of the ACM 48 (10), 83-90, 2005
Using data mining methods to build customer profiles
G Adomavicius, A Tuzhilin
Computer 34 (2), 74-82, 2001
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
Multi-criteria recommender systems
G Adomavicius, N Manouselis, YO Kwon
Recommender systems handbook, 769-803, 2011
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
Expert-driven validation of rule-based user models in personalization applications
G Adomavicius, A Tuzhilin
Data Mining and Knowledge Discovery 5 (1-2), 33-58, 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
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
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 (2), 185-202, 2007
Multidimensional recommender systems: a data warehousing approach
G Adomavicius, A Tuzhilin
International Workshop on Electronic Commerce, 180-192, 2001
Discovery of Actionable Patterns in Databases: The Action Hierarchy Approach.
G Adomavicius, A Tuzhilin
KDD, 111-114, 1997
Stability of recommendation algorithms
G Adomavicius, J Zhang
ACM Transactions on Information Systems (TOIS) 30 (4), 1-31, 2012
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
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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