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ICDE
2010
IEEE
222views Database» more  ICDE 2010»
10 years 12 months ago
Finding Clusters in subspaces of very large, multi-dimensional datasets
Abstract— We propose the Multi-resolution Correlation Cluster detection (MrCC), a novel, scalable method to detect correlation clusters able to analyze dimensional data in the ra...
Robson Leonardo Ferreira Cordeiro, Agma J. M. Trai...
SSDBM
2006
IEEE
123views Database» more  SSDBM 2006»
11 years 7 months ago
Mining Hierarchies of Correlation Clusters
The detection of correlations between different features in high dimensional data sets is a very important data mining task. These correlations can be arbitrarily complex: One or...
Elke Achtert, Christian Böhm, Peer Kröge...
PAKDD
2007
ACM
184views Data Mining» more  PAKDD 2007»
11 years 7 months ago
A Fast Algorithm for Finding Correlation Clusters in Noise Data
Abstract. Noise significantly affects cluster quality. Conventional clustering methods hardly detect clusters in a data set containing a large amount of noise. Projected clusterin...
Jiuyong Li, Xiaodi Huang, Clinton Selke, Jianming ...
SSDBM
2007
IEEE
110views Database» more  SSDBM 2007»
11 years 7 months ago
On Exploring Complex Relationships of Correlation Clusters
In high dimensional data, clusters often only exist in arbitrarily oriented subspaces of the feature space. In addition, these so-called correlation clusters may have complex rela...
Elke Achtert, Christian Böhm, Hans-Peter Krie...
KDD
2006
ACM
145views Data Mining» more  KDD 2006»
12 years 1 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
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