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Jiawei Han
Jiawei Han
Abel Bliss Professor of Computer Science, University of Illinois
E-mail confirmado em cs.uiuc.edu - Página inicial
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Data mining: concepts and techniques
J Han, J Pei, M Kamber
Elsevier, 2011
532402011
Mining frequent patterns without candidate generation
J Han, J Pei, Y Yin
ACM sigmod record 29 (2), 1-12, 2000
100262000
Data mining: an overview from a database perspective
MS Chen, J Han, PS Yu
IEEE Transactions on Knowledge and data Engineering 8 (6), 866-883, 1996
37251996
Mining frequent patterns without candidate generation: A frequent-pattern tree approach
J Han, J Pei, Y Yin, R Mao
Data mining and knowledge discovery 8 (1), 53-87, 2004
34512004
Prefixspan: Mining sequential patterns efficiently by prefix-projected pattern growth
J Han, J Pei, B Mortazavi-Asl, H Pinto, Q Chen, U Dayal, M Hsu
proceedings of the 17th international conference on data engineering, 215-224, 2001
33042001
E cient and E ective clustering methods for spatial data mining
RT Ng, J Han
Proceedings of VLDB, 144-155, 1994
32541994
Data mining concepts and techniques
H Jiawei, K Micheline, P Jian
29692016
gspan: Graph-based substructure pattern mining
X Yan, J Han
2002 IEEE International Conference on Data Mining, 2002. Proceedings., 721-724, 2002
28942002
A framework for clustering evolving data streams
CC Aggarwal, SY Philip, J Han, J Wang
Proceedings 2003 VLDB conference, 81-92, 2003
25192003
Graph regularized nonnegative matrix factorization for data representation
D Cai, X He, J Han, TS Huang
IEEE transactions on pattern analysis and machine intelligence 33 (8), 1548-1560, 2010
20782010
数据挖掘: 概念与技术
坎伯， 小峰
机械工业出版社, 2001
2012*2001
Mining concept-drifting data streams using ensemble classifiers
H Wang, W Fan, PS Yu, J Han
Proceedings of the ninth ACM SIGKDD international conference on Knowledge …, 2003
18172003
Trajectory clustering: a partition-and-group framework
JG Lee, J Han, KY Whang
Proceedings of the 2007 ACM SIGMOD international conference on Management of …, 2007
18072007
CMAR: Accurate and efficient classification based on multiple class-association rules
W Li, J Han, J Pei
Proceedings 2001 IEEE international conference on data mining, 369-376, 2001
17932001
Mining sequential patterns by pattern-growth: The prefixspan approach
J Pei, J Han, B Mortazavi-Asl, J Wang, H Pinto, Q Chen, U Dayal, MC Hsu
IEEE Transactions on knowledge and data engineering 16 (11), 1424-1440, 2004
17432004
Discovery of multiple-level association rules from large databases
J Han, Y Fu
VLDB 95, 420-431, 1995
17391995
Frequent pattern mining: current status and future directions
J Han, H Cheng, D Xin, X Yan
Data mining and knowledge discovery 15 (1), 55-86, 2007
17372007
Geographic data mining and knowledge discovery
HJ Miller, J Han
CRC press, 2009
1707*2009
Pathsim: Meta path-based top-k similarity search in heterogeneous information networks
Y Sun, J Han, X Yan, PS Yu, T Wu
Proceedings of the VLDB Endowment 4 (11), 992-1003, 2011
15562011
Maintenance of discovered association rules in large databases: An incremental updating technique
DW Cheung, J Han, VT Ng, CY Wong
Proceedings of the twelfth international conference on data engineering, 106-114, 1996
14241996
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