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KDD
1998
ACM
147views Data Mining» more  KDD 1998»
15 years 8 months ago
ADtrees for Fast Counting and for Fast Learning of Association Rules
Abstract: The problem of discovering association rules in large databases has received considerable research attention. Much research has examined the exhaustive discovery of all a...
Brigham S. Anderson, Andrew W. Moore
KDD
1998
ACM
145views Data Mining» more  KDD 1998»
15 years 8 months ago
Coincidence Detection: A Fast Method for Discovering Higher-Order Correlations in Multidimensional Data
Wepresent a novel, fast methodfor associationminingill high-dimensionaldatasets. OurCoincidence Detection method, which combines random sampling and Chernoff-Hoeffding bounds with...
Evan W. Steeg, Derek A. Robinson, Ed Willis
ICDIM
2008
IEEE
15 years 10 months ago
A fast approximate algorithm for large-scale Latent Semantic Indexing
Latent Semantic Indexing (LSI) is an effective method to discover the underlying semantic structure of data. It has numerous applications in information retrieval and data mining....
Dell Zhang, Zheng Zhu
KDD
2004
ACM
131views Data Mining» more  KDD 2004»
16 years 4 months ago
Fast nonlinear regression via eigenimages applied to galactic morphology
Astronomy increasingly faces the issue of massive datasets. For instance, the Sloan Digital Sky Survey (SDSS) has so far generated tens of millions of images of distant galaxies, ...
Brigham Anderson, Andrew W. Moore, Andrew Connolly...
KAIS
2006
126views more  KAIS 2006»
15 years 3 months ago
Fast and exact out-of-core and distributed k-means clustering
Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...
Ruoming Jin, Anjan Goswami, Gagan Agrawal