766 search results - page 2 / 154 » Clustering high dimensional data using subspace and projecte... |
ECML
2006
Springer
13 years 11 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
2012
SIAM
11 years 10 months ago
2012
SIAM
Clustering of high dimensional data streams is an important problem in many application domains, a prominent example being network monitoring. Several approaches have been lately ...
SIGMOD
1998
ACM
13 years 11 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...
SDM
2004
SIAM
13 years 8 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...
ICDM
2003
IEEE
14 years 22 days ago
2003
IEEE
We are proposing a novel method that makes it possible to analyze high dimensional data with arbitrary shaped projected clusters and high noise levels. At the core of our method l...