Alexander Tuzhilin

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Gediminas AdomaviciusProfessor of Information and Decision Sciences, University of Minnesota在 umn.edu 的电子邮件经过验证
Balaji PadmanabhanDean's Professor of Decision, Operations & Information Technologies at University of Maryland在 umd.edu 的电子邮件经过验证
Konstantin BaumanAssistant Professor, Fox School of Business, Temple University在 temple.edu 的电子邮件经过验证
Pan LiAssistant Professor, Scheller College of Business, Georgia Institute of Technology在 gatech.edu 的电子邮件经过验证
Panagiotis (Panos) AdamopoulosGoizueta Business School, Emory University在 stern.nyu.edu 的电子邮件经过验证
A SilberschatzProfessor of Computer Science at Yale University在 yale.edu 的电子邮件经过验证
Dr. Hui Xiong, Fellow of AAAS and IEEERutgers University/Baidu/HKUST在 ust.hk 的电子邮件经过验证
Yong GeAssociate Professor of MIS at University of Arizona在 email.arizona.edu 的电子邮件经过验证
Bing LiuDistinguished Professor, University of Illinois at Chicago在 uic.edu 的电子邮件经过验证
Bamshad MobasherSchool of Computing, DePaul University在 cs.depaul.edu 的电子邮件经过验证
Akhmed UmyarovUniversity of Minnesota. Carlson School of Management.在 umn.edu 的电子邮件经过验证
Dietmar JannachUniversity of Klagenfurt, Austria; University of Bergen, Norway在 aau.at 的电子邮件经过验证
Markus ZankerFree University of Bolzano-Bozen, Italy; University of Klagenfurt, Austria在 unibz.it 的电子邮件经过验证
Rong ZhengAssociate Professor of Information System, HKUST在 ust.hk 的电子邮件经过验证
Paul ResnickUniversity of Michigan在 umich.edu 的电子邮件经过验证
Michael J. PazzaniDistinguished Principal Scientist在 isi.edu 的电子邮件经过验证
Ke WangProfessor of Computing Science, Simon Fraser University在 cs.sfu.ca 的电子邮件经过验证
Ada Wai-Chee FuChinese University of Hong Kong在 cse.cuhk.edu.hk 的电子邮件经过验证
Ramesh ShankarAssociate Professor of Information Systems, University of Connecticut在 business.uconn.edu 的电子邮件经过验证

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Alexander Tuzhilin

Professor of Information Systems, NYU

在 stern.nyu.edu 的电子邮件经过验证

data mining machine learning personalization recommender systems information systems


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
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	15116	2005
Context-aware recommender systems G Adomavicius, A Tuzhilin Recommender systems handbook, 217-253, 2010	3315	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	1777	2005
System and method for dynamic profiling of users in one-to-one applications AS Tuzhilin US Patent 6,236,978, 2001	1219	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	1065	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	806*	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	612	2008
On subjective measures of interestingness in knowledge discovery. A Silberschatz, A Tuzhilin KDD 95, 275-281, 1995	609	1995
Personalization technologies: a process-oriented perspective G Adomavicius, A Tuzhilin Communications of the ACM 48 (10), 83-90, 2005	603	2005
Using data mining methods to build customer profiles G Adomavicius, A Tuzhilin Computer 34 (2), 74-82, 2001	450	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	439	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	395*	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	316	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	300	2009
Unexpectedness as a measure of interestingness in knowledge discovery B Padmanabhan, A Tuzhilin Decision Support Systems 27 (3), 303-318, 1999	295	1999
Ddtcdr: Deep dual transfer cross domain recommendation P Li, A Tuzhilin Proceedings of the 13th International Conference on Web Search and Data …, 2020	277	2020
Expert-driven validation of rule-based user models in personalization applications G Adomavicius, A Tuzhilin Data Mining and Knowledge Discovery 5, 33-58, 2001	273	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	241	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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