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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
ACMSE
2009
ACM
14 years 1 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
DAWAK
2004
Springer
14 years 23 days ago
Mining Maximal Frequently Changing Subtree Patterns from XML Documents
Abstract. Due to the dynamic nature of online information, XML documents typically evolve over time. The change of the data values or structures of an XML document may exhibit some...
Ling Chen 0002, Sourav S. Bhowmick, Liang-Tien Chi...
PAKDD
2005
ACM
100views Data Mining» more  PAKDD 2005»
14 years 26 days ago
Pushing Tougher Constraints in Frequent Pattern Mining
In this paper we extend the state-of-art of the constraints that can be pushed in a frequent pattern computation. We introduce a new class of tough constraints, namely Loose Anti-m...
Francesco Bonchi, Claudio Lucchese
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
14 years 7 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...