298 search results - page 6 / 60 » Subspace Clustering of High Dimensional Data |
175
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ICDE
2008
IEEE
15 years 11 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...
80
Voted
ICDM
2008
IEEE
15 years 4 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...
110
Voted
DASFAA
2007
IEEE
15 years 4 months ago
2007
IEEE
Subspace clustering (also called projected clustering) addresses the problem that different sets of attributes may be relevant for different clusters in high dimensional feature sp...
99
Voted
ICDE
2010
IEEE
14 years 8 months ago
2010
IEEE
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...
97
Voted
DEXA
2009
Springer
15 years 4 months ago
2009
Springer
Abstract. In this paper, we study the problem of projected outlier detection in high dimensional data streams and propose a new technique, called Stream Projected Ouliter deTector ...