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» Approximate data mining in very large relational data
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PAKDD
2010
ACM
173views Data Mining» more  PAKDD 2010»
13 years 5 months ago
Distributed Knowledge Discovery with Non Linear Dimensionality Reduction
Data mining tasks results are usually improved by reducing the dimensionality of data. This improvement however is achieved harder in the case that data lay on a non linear manifol...
Panagis Magdalinos, Michalis Vazirgiannis, Dialect...
BMCBI
2008
204views more  BMCBI 2008»
13 years 7 months ago
EST2uni: an open, parallel tool for automated EST analysis and database creation, with a data mining web interface and microarra
Background: Expressed sequence tag (EST) collections are composed of a high number of single-pass, redundant, partial sequences, which need to be processed, clustered, and annotat...
Javier Forment, Francisco Gilabert Villamón...
SDM
2012
SIAM
245views Data Mining» more  SDM 2012»
11 years 9 months ago
Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study
Low-rank approximations which are computed from selected rows and columns of a given data matrix have attracted considerable attention lately. They have been proposed as an altern...
Christian Thurau, Kristian Kersting, Christian Bau...
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 7 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang
SDM
2003
SIAM
183views Data Mining» more  SDM 2003»
13 years 8 months ago
ApproxMAP: Approximate Mining of Consensus Sequential Patterns
Conventional sequential pattern mining methods may meet inherent difficulties in mining databases with long sequences and noise. They may generate a huge number of short and trivi...
Hye-Chung Kum, Jian Pei, Wei Wang 0010, Dean Dunca...