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» Mining Patterns in Long Sequential Data with Noise
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KDD
2002
ACM
112views Data Mining» more  KDD 2002»
14 years 8 months ago
From run-time behavior to usage scenarios: an interaction-pattern mining approach
A key challenge facing IT organizations today is their evolution towards adopting e-business practices that gives rise to the need for reengineering their underlying software syst...
Mohammad El-Ramly, Eleni Stroulia, Paul G. Sorenso...
CORR
2008
Springer
115views Education» more  CORR 2008»
13 years 7 months ago
New probabilistic interest measures for association rules
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for ...
Michael Hahsler, Kurt Hornik
FIMI
2003
170views Data Mining» more  FIMI 2003»
13 years 9 months ago
kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets
This paper presents the implementation of kDCI, an enhancement of DCI [10], a scalable algorithm for discovering frequent sets in large databases. The main contribution of kDCI re...
Salvatore Orlando, Claudio Lucchese, Paolo Palmeri...
KDD
2005
ACM
178views Data Mining» more  KDD 2005»
14 years 1 months ago
Failure detection and localization in component based systems by online tracking
The increasing complexity of today’s systems makes fast and accurate failure detection essential for their use in mission-critical applications. Various monitoring methods provi...
Haifeng Chen, Guofei Jiang, Cristian Ungureanu, Ke...
RCIS
2010
13 years 6 months ago
A Tree-based Approach for Efficiently Mining Approximate Frequent Itemsets
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
Jia-Ling Koh, Yi-Lang Tu