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» Mining Supplemental Frequent Patterns
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ICDM
2007
IEEE
150views Data Mining» more  ICDM 2007»
14 years 4 months ago
Connections between Mining Frequent Itemsets and Learning Generative Models
Frequent itemsets mining is a popular framework for pattern discovery. In this framework, given a database of customer transactions, the task is to unearth all patterns in the for...
Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ra...
KDD
2008
ACM
239views Data Mining» more  KDD 2008»
14 years 10 months ago
Mining adaptively frequent closed unlabeled rooted trees in data streams
Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees a...
Albert Bifet, Ricard Gavaldà
ICDM
2002
IEEE
148views Data Mining» more  ICDM 2002»
14 years 2 months ago
SLPMiner: An Algorithm for Finding Frequent Sequential Patterns Using Length-Decreasing Support Constraint
Over the years, a variety of algorithms for finding frequent sequential patterns in very large sequential databases have been developed. The key feature in most of these algorith...
Masakazu Seno, George Karypis
JCST
2008
119views more  JCST 2008»
13 years 9 months ago
Mining Frequent Generalized Itemsets and Generalized Association Rules Without Redundancy
This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact ...
Daniel Kunkle, Donghui Zhang, Gene Cooperman
JIIS
2007
154views more  JIIS 2007»
13 years 9 months ago
Constraint-based sequential pattern mining: the pattern-growth methods
Constraints are essential for many sequential pattern mining applications. However, there is no systematic study on constraint-based sequential pattern mining. In this paper, we in...
Jian Pei, Jiawei Han, Wei Wang