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» Methods for finding frequent items in data streams
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KDD
2008
ACM
246views Data Mining» more  KDD 2008»
14 years 8 months ago
Direct mining of discriminative and essential frequent patterns via model-based search tree
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...
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
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 8 months ago
Real-time ranking with concept drift using expert advice
In many practical applications, one is interested in generating a ranked list of items using information mined from continuous streams of data. For example, in the context of comp...
Hila Becker, Marta Arias
PAKDD
2010
ACM
171views Data Mining» more  PAKDD 2010»
13 years 6 months ago
Summarizing Multidimensional Data Streams: A Hierarchy-Graph-Based Approach
With the rapid development of information technology, many applications have to deal with potentially infinite data streams. In such a dynamic context, storing the whole data stre...
Yoann Pitarch, Anne Laurent, Pascal Poncelet
COMPSAC
2005
IEEE
13 years 9 months ago
A Novel Method for Protecting Sensitive Knowledge in Association Rules Mining
Discovering frequent patterns from huge amounts of data is one of the most studied problems in data mining. However, some sensitive patterns with security policies may cause a thr...
En Tzu Wang, Guanling Lee, Yu Tzu Lin