847 search results - page 5 / 170 » Approximation algorithms for projective clustering |
SIGMOD
2000
ACM
13 years 11 months ago
2000
ACM
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
KAIS
2011
13 years 2 months ago
2011
Triangle counting is an important problem in graph mining. Two frequently used metrics in complex network analysis which require the count of triangles are the clustering coefficie...
INCDM
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Clustering algorithms for multidimensional numerical data must overcome special difficulties due to the irregularities of data distribution. We present a clustering algo...
BIBE
2004
IEEE
13 years 11 months ago
2004
IEEE
In microarray gene expression data, clusters may hide in subspaces. Traditional clustering algorithms that make use of similarity measurements in the full input space may fail to ...
ICPR
2004
IEEE
14 years 8 months ago
2004
IEEE
We define a cluster to be characterized by regions of high density separated by regions that are sparse. By observing the downward closure property of density, the search for inte...