Alexander Tuzhilin

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Gediminas AdomaviciusProfessor of Information and Decision Sciences, University of MinnesotaVerified email at umn.edu
Balaji PadmanabhanDean's Professor of Decision, Operations & Information Technologies at University of MarylandVerified email at umd.edu
Konstantin BaumanAssistant Professor, Fox School of Business, Temple UniversityVerified email at temple.edu
Pan LiAssistant Professor, Scheller College of Business, Georgia Institute of TechnologyVerified email at gatech.edu
Panagiotis (Panos) AdamopoulosGoizueta Business School, Emory UniversityVerified email at stern.nyu.edu
A SilberschatzProfessor of Computer Science at Yale UniversityVerified email at yale.edu
Dr. Hui Xiong, Fellow of AAAS and IEEERutgers University/Baidu/HKUSTVerified email at ust.hk
Yong GeAssociate Professor of MIS at University of ArizonaVerified email at email.arizona.edu
Bing LiuDistinguished Professor, University of Illinois at ChicagoVerified email at uic.edu
Akhmed UmyarovUniversity of Minnesota. Carlson School of Management.Verified email at umn.edu
Bamshad MobasherSchool of Computing, DePaul UniversityVerified email at cs.depaul.edu
Dietmar JannachUniversity of Klagenfurt, Austria; University of Bergen, NorwayVerified email at aau.at
Markus ZankerFree University of Bolzano-Bozen, Italy; University of Klagenfurt, AustriaVerified email at unibz.it
Rong ZhengAssociate Professor of Information System, HKUSTVerified email at ust.hk
Paul ResnickUniversity of MichiganVerified email at umich.edu
Michael J. PazzaniDistinguished Principal ScientistVerified email at isi.edu
Ke WangProfessor of Computing Science, Simon Fraser UniversityVerified email at cs.sfu.ca
Ada Wai-Chee FuChinese University of Hong KongVerified email at cse.cuhk.edu.hk
Ramesh ShankarAssociate Professor of Information Systems, University of ConnecticutVerified email at business.uconn.edu

Alexander Tuzhilin

Professor of Information Systems, NYU

Verified email at stern.nyu.edu

data mining machine learning personalization recommender systems information systems


Title Sort by citations Sort by year Sort by 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	14943	2005
Context-aware recommender systems G Adomavicius, A Tuzhilin Recommender systems handbook, 217-253, 2010	3277	2010
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	1767	2005
System and method for dynamic profiling of users in one-to-one applications AS Tuzhilin US Patent 6,236,978, 2001	1213	2001
What makes patterns interesting in knowledge discovery systems A Silberschatz, A Tuzhilin IEEE Transactions on Knowledge and data engineering 8 (6), 970-974, 1996	1061	1996
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	800*	2009
On subjective measures of interestingness in knowledge discovery. A Silberschatz, A Tuzhilin KDD 95, 275-281, 1995	609	1995
The long tail of recommender systems and how to leverage it YJ Park, A Tuzhilin Proceedings of the 2008 ACM conference on Recommender systems, 11-18, 2008	599	2008
Personalization technologies: a process-oriented perspective G Adomavicius, A Tuzhilin Communications of the ACM 48 (10), 83-90, 2005	595	2005
Using data mining methods to build customer profiles G Adomavicius, A Tuzhilin Computer 34 (2), 74-82, 2001	443	2001
An energy-efficient mobile recommender system Y Ge, H Xiong, A Tuzhilin, K Xiao, M Gruteser, M Pazzani Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010	438	2010
A Belief-Driven Method for Discovering Unexpected Patterns. B Padmanabhan, A Tuzhilin KDD 98, 94-100, 1998	393	1998
On unexpectedness in recommender systems: Or how to except the unexpected P Adamopoulos, A Tuzhilin RecSys Workshop on Novelty and Diversity in Recommender Systems, 2011	389*	2011
Using context to improve predictive modeling of customers in personalization applications C Palmisano, A Tuzhilin, M Gorgoglione IEEE transactions on knowledge and data engineering 20 (11), 1535-1549, 2008	315	2008
Experimental comparison of pre-vs. post-filtering approaches in context-aware recommender systems U Panniello, A Tuzhilin, M Gorgoglione, C Palmisano, A Pedone Proceedings of the third ACM conference on Recommender systems, 265-268, 2009	298	2009
Unexpectedness as a measure of interestingness in knowledge discovery B Padmanabhan, A Tuzhilin Decision Support Systems 27 (3), 303-318, 1999	295	1999
Expert-driven validation of rule-based user models in personalization applications G Adomavicius, A Tuzhilin Data Mining and Knowledge Discovery 5, 33-58, 2001	270	2001
Ddtcdr: Deep dual transfer cross domain recommendation P Li, A Tuzhilin Proceedings of the 13th International Conference on Web Search and Data …, 2020	262	2020
Aspect based recommendations: Recommending items with the most valuable aspects based on user reviews K Bauman, B Liu, A Tuzhilin Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017	236	2017
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

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