Alexander Tuzhilin

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Gediminas AdomaviciusProfessor of Information and Decision Sciences, University of Minnesota確認したメールアドレス: umn.edu
Balaji PadmanabhanDirector, Center for Artificial Intelligence in Business確認したメールアドレス: umd.edu
Pan LiAssistant Professor, Scheller College of Business, Georgia Institute of Technology確認したメールアドレス: gatech.edu
Konstantin BaumanAssistant Professor, Fox School of Business, Temple University確認したメールアドレス: temple.edu
Panagiotis (Panos) AdamopoulosGoizueta Business School, Emory University確認したメールアドレス: stern.nyu.edu
A SilberschatzProfessor of Computer Science at Yale University確認したメールアドレス: yale.edu
Dr. Hui Xiong, Fellow of AAAS, AAAI a...Rutgers University/Baidu/HKUST確認したメールアドレス: ust.hk
Bing LiuDistinguished Professor, University of Illinois at Chicago確認したメールアドレス: uic.edu
Yong GeAssociate Professor of MIS at University of Arizona確認したメールアドレス: email.arizona.edu
Bamshad MobasherSchool of Computing, DePaul University確認したメールアドレス: cs.depaul.edu
Akhmed UmyarovUniversity of Minnesota. Carlson School of Management.確認したメールアドレス: umn.edu
Dietmar JannachUniversity of Klagenfurt, Austria; University of Bergen, Norway確認したメールアドレス: aau.at
Markus ZankerFree University of Bolzano-Bozen, Italy; University of Klagenfurt, Austria確認したメールアドレス: unibz.it
Rong ZhengAssociate Professor of Information System, HKUST確認したメールアドレス: ust.hk
Paul ResnickUniversity of Michigan確認したメールアドレス: umich.edu
Michael J. PazzaniDistinguished Principal Scientist確認したメールアドレス: isi.edu
Ke WangProfessor of Computing Science, Simon Fraser University確認したメールアドレス: cs.sfu.ca
Ada Wai-Chee FuChinese University of Hong Kong確認したメールアドレス: cse.cuhk.edu.hk
Ramesh ShankarAssociate Professor of Information Systems, University of Connecticut確認したメールアドレス: business.uconn.edu

フォロー

Alexander Tuzhilin

Professor of Information Systems, NYU

確認したメールアドレス: stern.nyu.edu

data mining machine learning personalization recommender systems information systems


タイトル引用回数順公開年順タイトル順	引用先引用先	年
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	15234	2005
Context-aware recommender systems G Adomavicius, A Tuzhilin Recommender systems handbook, 217-253, 2010	3356	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	1764	2005
System and method for dynamic profiling of users in one-to-one applications AS Tuzhilin US Patent 6,236,978, 2001	1232	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	1088	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	819*	2009
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	636	2008
On subjective measures of interestingness in knowledge discovery. A Silberschatz, A Tuzhilin KDD 95, 275-281, 1995	611	1995
Personalization technologies: a process-oriented perspective G Adomavicius, A Tuzhilin Communications of the ACM 48 (10), 83-90, 2005	608	2005
Using data mining methods to build customer profiles G Adomavicius, A Tuzhilin Computer 34 (2), 74-82, 2001	448	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	436	2010
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	397*	2011
A Belief-Driven Method for Discovering Unexpected Patterns. B Padmanabhan, A Tuzhilin KDD 98, 94-100, 1998	393	1998
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	317	2008
Ddtcdr: Deep dual transfer cross domain recommendation P Li, A Tuzhilin Proceedings of the 13th international conference on web search and data …, 2020	305	2020
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	296	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	282	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	247	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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