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» Mining Patterns in Long Sequential Data with Noise
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ICDM
2007
IEEE
169views Data Mining» more  ICDM 2007»
13 years 11 months ago
Efficient Discovery of Frequent Approximate Sequential Patterns
We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "brea...
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu
WWW
2008
ACM
14 years 8 months ago
Efficient mining of frequent sequence generators
Sequential pattern mining has raised great interest in data mining research field in recent years. However, to our best knowledge, no existing work studies the problem of frequent...
Chuancong Gao, Jianyong Wang, Yukai He, Lizhu Zhou
ACMSE
2009
ACM
14 years 2 months ago
A hybrid approach to mining frequent sequential patterns
The mining of frequent sequential patterns has been a hot and well studied area—under the broad umbrella of research known as KDD (Knowledge Discovery and Data Mining)— for we...
Erich Allen Peterson, Peiyi Tang
KDD
2005
ACM
170views Data Mining» more  KDD 2005»
14 years 8 months ago
Parallel mining of closed sequential patterns
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most u...
Shengnan Cong, Jiawei Han, David A. Padua
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 8 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos