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» Subspace Clustering of High Dimensional Data
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KDD
2005
ACM
142views Data Mining» more  KDD 2005»
16 years 4 months ago
Towards exploratory test instance specific algorithms for high dimensional classification
In an interactive classification application, a user may find it more valuable to develop a diagnostic decision support method which can reveal significant classification behavior...
Charu C. Aggarwal
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
16 years 4 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...
ISCA
2007
IEEE
217views Hardware» more  ISCA 2007»
15 years 4 months ago
Parallel Processing of High-Dimensional Remote Sensing Images Using Cluster Computer Architectures
Hyperspectral sensors represent the most advanced instruments currently available for remote sensing of the Earth. The high spatial and spectral resolution of the images supplied ...
David Valencia, Antonio Plaza, Pablo Martín...
EDBT
2006
ACM
182views Database» more  EDBT 2006»
16 years 4 months ago
On High Dimensional Skylines
In many decision-making applications, the skyline query is frequently used to find a set of dominating data points (called skyline points) in a multidimensional dataset. In a high-...
Chee Yong Chan, H. V. Jagadish, Kian-Lee Tan, Anth...
CIKM
2003
Springer
15 years 9 months ago
Dimensionality reduction using magnitude and shape approximations
High dimensional data sets are encountered in many modern database applications. The usual approach is to construct a summary of the data set through a lossy compression technique...
Ümit Y. Ogras, Hakan Ferhatosmanoglu