Alexander Tuzhilin

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Gediminas AdomaviciusProfessor of Information and Decision Sciences, University of MinnesotaDirección de correo verificada de umn.edu
Balaji PadmanabhanDean's Professor of Decision, Operations & Information Technologies at University of MarylandDirección de correo verificada de umd.edu
Konstantin BaumanAssistant Professor, Fox School of Business, Temple UniversityDirección de correo verificada de temple.edu
Pan LiAssistant Professor, Scheller College of Business, Georgia Institute of TechnologyDirección de correo verificada de gatech.edu
Panagiotis (Panos) AdamopoulosGoizueta Business School, Emory UniversityDirección de correo verificada de stern.nyu.edu
A SilberschatzProfessor of Computer Science at Yale UniversityDirección de correo verificada de yale.edu
Hui Xiong, Fellow of AAAS and IEEERutgers University/Baidu/HKUSTDirección de correo verificada de ust.hk
Yong GeAssociate Professor of MIS at University of ArizonaDirección de correo verificada de email.arizona.edu
Bing LiuDistinguished Professor, University of Illinois at ChicagoDirección de correo verificada de uic.edu
Bamshad MobasherSchool of Computing, DePaul UniversityDirección de correo verificada de cs.depaul.edu
Akhmed UmyarovUniversity of Minnesota. Carlson School of Management.Dirección de correo verificada de umn.edu
Dietmar JannachUniversity of Klagenfurt, Austria; University of Bergen, NorwayDirección de correo verificada de aau.at
Markus ZankerFree University of Bolzano-Bozen, Italy; University of Klagenfurt, AustriaDirección de correo verificada de unibz.it
Rong ZhengAssociate Professor of Information System, HKUSTDirección de correo verificada de ust.hk
Paul ResnickUniversity of MichiganDirección de correo verificada de umich.edu
Michael J. PazzaniDistinguished Principal ScientistDirección de correo verificada de isi.edu
Ke WangProfessor of Computing Science, Simon Fraser UniversityDirección de correo verificada de cs.sfu.ca
Ada Wai-Chee FuChinese University of Hong KongDirección de correo verificada de cse.cuhk.edu.hk
Ramesh ShankarAssociate Professor of Information Systems, University of ConnecticutDirección de correo verificada de business.uconn.edu

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Alexander Tuzhilin

Professor of Information Systems, NYU

Dirección de correo verificada de stern.nyu.edu

data mining machine learning personalization recommender systems information systems


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	14628	2005
Context-aware recommender systems G Adomavicius, A Tuzhilin Recommender systems handbook, 217-253, 2010	3207	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	1746	2005
System and method for dynamic profiling of users in one-to-one applications AS Tuzhilin US Patent 6,236,978, 2001	1195	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	1054	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	781*	2009
On subjective measures of interestingness in knowledge discovery. A Silberschatz, A Tuzhilin KDD 95, 275-281, 1995	605	1995
Personalization technologies: a process-oriented perspective G Adomavicius, A Tuzhilin Communications of the ACM 48 (10), 83-90, 2005	586	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	578	2008
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	434	2010
Using data mining methods to build customer profiles G Adomavicius, A Tuzhilin Computer 34 (2), 74-82, 2001	430	2001
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	377*	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	313	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	293	2009
Unexpectedness as a measure of interestingness in knowledge discovery B Padmanabhan, A Tuzhilin Decision Support Systems 27 (3), 303-318, 1999	293	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
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	228	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	224	1999
Ddtcdr: Deep dual transfer cross domain recommendation P Li, A Tuzhilin Proceedings of the 13th International Conference on Web Search and Data …, 2020	223	2020

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