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» Visually Mining through Cluster Hierarchies
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SDM
2004
SIAM
141views Data Mining» more  SDM 2004»
13 years 5 months ago
Visually Mining through Cluster Hierarchies
Similarity search in database systems is becoming an increasingly important task in modern application domains such as multimedia, molecular biology, medical imaging, computer aid...
Stefan Brecheisen, Hans-Peter Kriegel, Peer Kr&oum...
ICDM
2005
IEEE
138views Data Mining» more  ICDM 2005»
13 years 10 months ago
On Feature Selection through Clustering
We study an algorithm for feature selection that clusters attributes using a special metric and then makes use of the dendrogram of the resulting cluster hierarchy to choose the m...
Richard Butterworth, Gregory Piatetsky-Shapiro, Da...
SSDBM
2006
IEEE
123views Database» more  SSDBM 2006»
13 years 10 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...
ICDM
2006
IEEE
161views Data Mining» more  ICDM 2006»
13 years 10 months ago
Hierarchical Density Shaving: A clustering and visualization framework for large biological datasets
In many clustering applications for bioinformatics, only part of the data clusters into one or more groups while the rest needs to be pruned. For such situations, we present Hiera...
Gunjan Gupta, Alexander Liu, Joydeep Ghosh
IEAAIE
2005
Springer
13 years 10 months ago
Analyzing Multi-level Spatial Association Rules Through a Graph-Based Visualization
Association rules discovery is a fundamental task in spatial data mining where data are naturally described at multiple levels of granularity. ARES is a spatial data mining system ...
Annalisa Appice, Paolo Buono