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» Discovering frequent patterns in sensitive data
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ICMCS
2009
IEEE
199views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Association rule mining in multiple, multidimensional time series medical data
Time series pattern mining (TSPM) finds correlations or dependencies in same series or in multiple time series. When the numerous instances of multiple time series data are associ...
Gaurav N. Pradhan, B. Prabhakaran
ICTAI
2006
IEEE
14 years 1 months ago
Sequence Mining Without Sequences: A New Way for Privacy Preserving
During the last decade, sequential pattern mining has been the core of numerous researches. It is now possible to efficiently discover users’ behavior in various domains such a...
Stéphanie Jacquemont, François Jacqu...
KDD
1998
ACM
105views Data Mining» more  KDD 1998»
13 years 11 months ago
PlanMine: Sequence Mining for Plan Failures
This paper presents the PLANMINE sequence mining algorithm to extract patterns of events that predict failures in databases of plan executions. New techniques were needed because ...
Mohammed Javeed Zaki, Neal Lesh, Mitsunori Ogihara
ICASSP
2011
IEEE
12 years 11 months ago
Towards robust word discovery by self-similarity matrix comparison
Word discovery is the task of discovering and collecting occurrences of repeating words in the absence of prior acoustic and linguistic knowledge, or training material. The capabi...
Armando Muscariello, Guillaume Gravier, Fré...
ICDM
2009
IEEE
145views Data Mining» more  ICDM 2009»
13 years 5 months ago
Significance of Episodes Based on Minimal Windows
Discovering episodes, frequent sets of events from a sequence has been an active field in pattern mining. Traditionally, a level-wise approach is used to discover all frequent epis...
Nikolaj Tatti