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142
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KDD
2006
ACM
198views Data Mining» more  KDD 2006»
16 years 4 months ago
CFI-Stream: mining closed frequent itemsets in data streams
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
Nan Jiang, Le Gruenwald
145
Voted
KDD
2006
ACM
157views Data Mining» more  KDD 2006»
16 years 4 months ago
Using structure indices for efficient approximation of network properties
Statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the Internet. Calculating man...
Matthew J. Rattigan, Marc Maier, David Jensen
125
Voted
KDD
2006
ACM
153views Data Mining» more  KDD 2006»
16 years 4 months ago
Semi-supervised time series classification
The problem of time series classification has attracted great interest in the last decade. However current research assumes the existence of large amounts of labeled training data...
Li Wei, Eamonn J. Keogh
103
Voted
KDD
2005
ACM
109views Data Mining» more  KDD 2005»
16 years 4 months ago
Formulating distance functions via the kernel trick
Tasks of data mining and information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be for...
Gang Wu, Edward Y. Chang, Navneet Panda
143
Voted
KDD
2002
ACM
179views Data Mining» more  KDD 2002»
16 years 4 months ago
Combining clustering and co-training to enhance text classification using unlabelled data
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
Bhavani Raskutti, Herman L. Ferrá, Adam Kow...
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