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» Efficient Discovery of Confounders in Large Data Sets
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EDBT
2000
ACM
14 years 2 months ago
Mining Classification Rules from Datasets with Large Number of Many-Valued Attributes
Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
Giovanni Giuffrida, Wesley W. Chu, Dominique M. Ha...
ICCS
2003
Springer
14 years 3 months ago
A Compress-Based Association Mining Algorithm for Large Dataset
The association mining is one of the primary sub-areas in the field of data mining. This technique had been used in numerous practical applications, including consumer market baske...
Mafruz Zaman Ashrafi, David Taniar, Kate A. Smith
CORR
2010
Springer
173views Education» more  CORR 2010»
13 years 10 months ago
CONCISE: Compressed 'n' Composable Integer Set
Bit arrays, or bitmaps, are used to significantly speed up set operations in several areas, such as data warehousing, information retrieval, and data mining, to cite a few. Howeve...
Alessandro Colantonio, Roberto Di Pietro
SIGMOD
2001
ACM
193views Database» more  SIGMOD 2001»
14 years 10 months ago
Epsilon Grid Order: An Algorithm for the Similarity Join on Massive High-Dimensional Data
The similarity join is an important database primitive which has been successfully applied to speed up applications such as similarity search, data analysis and data mining. The s...
Christian Böhm, Bernhard Braunmüller, Fl...
LISA
2008
14 years 22 days ago
IZO: Applications of Large-Window Compression to Virtual Machine Management
The increased use of virtual machines in the enterprise environment presents an interesting new set of challenges for the administrators of today's information systems. In ad...
Mark A. Smith, Jan Pieper, Daniel Gruhl, Lucas Vil...