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KDD
2006
ACM
123views Data Mining» more  KDD 2006»
16 years 4 months ago
Mining rank-correlated sets of numerical attributes
We study the mining of interesting patterns in the presence of numerical attributes. Instead of the usual discretization methods, we propose the use of rank based measures to scor...
Toon Calders, Bart Goethals, Szymon Jaroszewicz
ICDM
2008
IEEE
130views Data Mining» more  ICDM 2008»
15 years 10 months ago
Mining Temporal Patterns with Quantitative Intervals
In this paper we consider the problem of discovering frequent temporal patterns in a database of temporal sequences, where a temporal sequence is a set of items with associated da...
Thomas Guyet, Rene Quiniou
138
Voted
ICDM
2007
IEEE
157views Data Mining» more  ICDM 2007»
15 years 5 months ago
Training Conditional Random Fields by Periodic Step Size Adaptation for Large-Scale Text Mining
For applications with consecutive incoming training examples, on-line learning has the potential to achieve a likelihood as high as off-line learning without scanning all availabl...
Han-Shen Huang, Yu-Ming Chang, Chun-Nan Hsu
122
Voted
SDM
2003
SIAM
120views Data Mining» more  SDM 2003»
15 years 5 months ago
Estimation of Topological Dimension
We present two extensions of the algorithm by Broomhead et al [2] which is based on the idea that singular values that scale linearly with the radius of the data ball can be explo...
Douglas R. Hundley, Michael J. Kirby
124
Voted
IDEAL
2003
Springer
15 years 8 months ago
Experiences of Using a Quantitative Approach for Mining Association Rules
In recent years interest has grown in “mining” large databases to extract novel and interesting information. Knowledge Discovery in Databases (KDD) has been recognised as an em...
L. Dong, Christos Tjortjis