30 search results - page 3 / 6 » Density-Connected Subspace Clustering for High-Dimensional D... |
SIGMOD
1998
ACM
13 years 9 months ago
1998
ACM
Data mining applications place special requirements on clustering algorithms including: the ability to nd clusters embedded in subspaces of high dimensional data, scalability, end...
ICDE
2008
IEEE
14 years 6 months ago
2008
IEEE
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
ICDM
2008
IEEE
13 years 11 months ago
2008
IEEE
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
ECML
2006
Springer
13 years 9 months ago
2006
Springer
A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
SDM
2004
SIAM
13 years 6 months ago
2004
SIAM
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...