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ASC
2011
13 years 8 days ago
A rough set approach to multiple dataset analysis
In the area of data mining, the discovery of valuable changes and connections (e.g., causality) from multiple data sets has been recognized as an important issue. This issue essen...
Ken Kaneiwa
ICDE
2008
IEEE
141views Database» more  ICDE 2008»
14 years 6 months ago
A General Framework for Fast Co-clustering on Large Datasets Using Matrix Decomposition
Abstract-- Simultaneously clustering columns and rows (coclustering) of large data matrix is an important problem with wide applications, such as document mining, microarray analys...
Feng Pan, Xiang Zhang, Wei Wang 0010
KDD
1995
ACM
148views Data Mining» more  KDD 1995»
13 years 8 months ago
Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
Philip K. Chan, Salvatore J. Stolfo
ICDM
2006
IEEE
130views Data Mining» more  ICDM 2006»
13 years 11 months ago
A Framework for Regional Association Rule Mining in Spatial Datasets
The immense explosion of geographically referenced data calls for efficient discovery of spatial knowledge. One critical requirement for spatial data mining is the capability to ...
Wei Ding 0003, Christoph F. Eick, Jing Wang 0007, ...
ICDM
2003
IEEE
114views Data Mining» more  ICDM 2003»
13 years 10 months ago
Unsupervised Link Discovery in Multi-relational Data via Rarity Analysis
A significant portion of knowledge discovery and data mining research focuses on finding patterns of interest in data. Once a pattern is found, it can be used to recognize satisfy...
Shou-de Lin, Hans Chalupsky