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Alexander Tuzhilin
Alexander Tuzhilin
Professor of Information Systems, NYU
Bestätigte E-Mail-Adresse bei stern.nyu.edu
Titel
Zitiert von
Zitiert von
Jahr
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
152412005
Context-aware recommender systems
G Adomavicius, A Tuzhilin
Recommender systems handbook, 217-253, 2010
33592010
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
17642005
System and method for dynamic profiling of users in one-to-one applications
AS Tuzhilin
US Patent 6,236,978, 2001
12322001
What makes patterns interesting in knowledge discovery systems
A Silberschatz, A Tuzhilin
IEEE Transactions on Knowledge and data engineering 8 (6), 970-974, 1996
10881996
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
6372008
On subjective measures of interestingness in knowledge discovery.
A Silberschatz, A Tuzhilin
KDD 95, 275-281, 1995
6111995
Personalization technologies: a process-oriented perspective
G Adomavicius, A Tuzhilin
Communications of the ACM 48 (10), 83-90, 2005
6082005
Using data mining methods to build customer profiles
G Adomavicius, A Tuzhilin
Computer 34 (2), 74-82, 2001
4482001
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
4362010
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
3931998
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
3172008
Ddtcdr: Deep dual transfer cross domain recommendation
P Li, A Tuzhilin
Proceedings of the 13th international conference on web search and data …, 2020
3062020
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
2962009
Unexpectedness as a measure of interestingness in knowledge discovery
B Padmanabhan, A Tuzhilin
Decision Support Systems 27 (3), 303-318, 1999
2931999
Expert-driven validation of rule-based user models in personalization applications
G Adomavicius, A Tuzhilin
Data Mining and Knowledge Discovery 5, 33-58, 2001
2822001
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
2482017
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
2281999
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