Clustering high-dimensional data

Known as: Subspace clustering 
Clustering high-dimensional data is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions. Such high… (More)
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Association rule learningBiclusteringBioinformaticsCorrelation clustering
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Cluster analysis

Papers overview

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2012
2012
Dimension Selective Self-Organizing Maps for clustering high dimensional data
High dimensional datasets usually present several dimensions which are irrelevant for certain clusters while they are relevant to… (More)
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2010
2010
Clustering high dimensional data using subspace and projected clustering algorithms
Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining… (More)
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Highly Cited
2007
Highly Cited
2007
High-dimensional data clustering
Clustering in high-dimensional spaces is a difficult problem which is recurrent in many domains, for example in image analysis… (More)
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2006
2006
A Fuzzy Subspace Algorithm for Clustering High Dimensional Data
In fuzzy clustering algorithms each object has a fuzzy membership associated with each cluster indicating the degree of… (More)
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Highly Cited
2005
Highly Cited
2005
Automatic Subspace Clustering of High Dimensional Data
Data mining applications place special requirements on clustering algorithms including: the ability to find clusters embedded in… (More)
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2004
2004
Subspace selection for clustering high-dimensional data
In high-dimensional feature spaces traditional clustering algorithms tend to break down in terms of efficiency and quality… (More)
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Highly Cited
2004
Highly Cited
2004
Subspace Clustering of High Dimensional Data
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance… (More)
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Highly Cited
2004
Highly Cited
2004
Density-Connected Subspace Clustering for High-Dimensional Data
Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be… (More)
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Highly Cited
2000
Highly Cited
2000
High-Dimensional Data Analysis : The Curses and Blessings of Dimensionality
The coming century is surely the century of data. A combination of blind faith and serious purpose makes our society invest… (More)
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Highly Cited
1998
Highly Cited
1998
Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications
Data mining applications place special requirements on clustering algorithms including: the ability to find clusters embedded in… (More)
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