Alexander Tuzhilin

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Gediminas AdomaviciusProfessor of Information and Decision Sciences, University of MinnesotaAdresse e-mail validée de umn.edu
Balaji PadmanabhanAnderson Professor of Global Management at University of South FloridaAdresse e-mail validée de usf.edu
Konstantin BaumanAssistant Professor, Fox School of Business, Temple UniversityAdresse e-mail validée de temple.edu
Panagiotis (Panos) AdamopoulosGoizueta Business School, Emory UniversityAdresse e-mail validée de stern.nyu.edu
A SilberschatzProfessor of Computer Science at Yale UniversityAdresse e-mail validée de yale.edu
Pan LiPhD, New York University, Stern School of BusinessAdresse e-mail validée de stern.nyu.edu
Hui Xiong, Fellow of AAAS and IEEERutgers University/Baidu/HKUSTAdresse e-mail validée de rutgers.edu
Yong GeAssociate Professor of MIS at University of ArizonaAdresse e-mail validée de email.arizona.edu
Bing LiuDistinguished Professor, University of Illinois at ChicagoAdresse e-mail validée de uic.edu
Bamshad MobasherSchool of Computing, DePaul UniversityAdresse e-mail validée de cs.depaul.edu
Akhmed UmyarovUniversity of Minnesota. Carlson School of Management.Adresse e-mail validée de umn.edu
Rong ZhengAssociate Professor of Information System, HKUSTAdresse e-mail validée de ust.hk
Michael J. PazzaniDistinguished ScientistAdresse e-mail validée de UCSD.edu
Dietmar JannachUniversity of Klagenfurt, Austria; University of Bergen, NorwayAdresse e-mail validée de aau.at
Markus ZankerFree University of Bolzano-Bozen, Italy; University of Klagenfurt, AustriaAdresse e-mail validée de unibz.it
Ke WangProfessor of Computing Science, Simon Fraser UniversityAdresse e-mail validée de cs.sfu.ca
Paul ResnickUniversity of MichiganAdresse e-mail validée de umich.edu
Ada Wai-Chee FuChinese University of Hong KongAdresse e-mail validée de cse.cuhk.edu.hk
Ramesh ShankarAssociate Professor of Information Systems, University of ConnecticutAdresse e-mail validée de business.uconn.edu

Suivre

Alexander Tuzhilin

Professor of Information Systems, NYU

Adresse e-mail validée de stern.nyu.edu

data mining machine learning personalization recommender systems information systems


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	13705	2005
Context-aware recommender systems G Adomavicius, A Tuzhilin Recommender systems handbook, 217-253, 2010	2961	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	1694	2005
System and method for dynamic profiling of users in one-to-one applications AS Tuzhilin US Patent 6,236,978, 2001	1150	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	1043	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	739*	2009
On subjective measures of interestingness in knowledge discovery. A Silberschatz, A Tuzhilin KDD 95, 275-281, 1995	595	1995
Personalization technologies: a process-oriented perspective G Adomavicius, A Tuzhilin Communications of the ACM 48 (10), 83-90, 2005	542	2005
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	482	2008
Using data mining methods to build customer profiles G Adomavicius, A Tuzhilin Computer 34 (2), 74-82, 2001	423	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	410	2010
A Belief-Driven Method for Discovering Unexpected Patterns. B Padmanabhan, A Tuzhilin KDD 98, 94-100, 1998	379	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	320*	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	300	2008
Unexpectedness as a measure of interestingness in knowledge discovery B Padmanabhan, A Tuzhilin Decision Support Systems 27 (3), 303-318, 1999	285	1999
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	275	2009
Expert-driven validation of rule-based user models in personalization applications G Adomavicius, A Tuzhilin Data Mining and Knowledge Discovery 5, 33-58, 2001	258	2001
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	215	1999
Small is beautiful: discovering the minimal set of unexpected patterns B Padmanabhan, A Tuzhilin Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000	200	2000
Comparing context-aware recommender systems in terms of accuracy and diversity U Panniello, A Tuzhilin, M Gorgoglione User Modeling and User-Adapted Interaction 24, 35-65, 2014	183	2014

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