Alexander Tuzhilin

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	Wszystkie	Od 2019
Cytowania	34607	10602
h-indeks	58	33
i10-indeks	126	74

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

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Alexander Tuzhilin

Professor of Information Systems, NYU

Zweryfikowany adres z stern.nyu.edu

data mining machine learning personalization recommender systems information systems


Tytuł Sortuj wg cytatów Sortuj wg roku Sortuj wg tytułu	Cytowane przez Cytowane przez	Rok
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	14968	2005
Context-aware recommender systems G Adomavicius, A Tuzhilin Recommender systems handbook, 217-253, 2010	3290	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	1770	2005
System and method for dynamic profiling of users in one-to-one applications AS Tuzhilin US Patent 6,236,978, 2001	1214	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	801*	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	601	2008
Personalization technologies: a process-oriented perspective G Adomavicius, A Tuzhilin Communications of the ACM 48 (10), 83-90, 2005	597	2005
Using data mining methods to build customer profiles G Adomavicius, A Tuzhilin Computer 34 (2), 74-82, 2001	446	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	299	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	271	2001
Ddtcdr: Deep dual transfer cross domain recommendation P Li, A Tuzhilin Proceedings of the 13th International Conference on Web Search and Data …, 2020	267	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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