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» Using the fractal dimension to cluster datasets
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ICDE
2007
IEEE
211views Database» more  ICDE 2007»
14 years 1 months ago
Document Representation and Dimension Reduction for Text Clustering
Increasingly large text datasets and the high dimensionality associated with natural language create a great challenge in text mining. In this research, a systematic study is cond...
M. Mahdi Shafiei, Singer Wang, Roger Zhang, Evange...
SC
2004
ACM
14 years 26 days ago
A Parallel Implementation of 4-Dimensional Haralick Texture Analysis for Disk-Resident Image Datasets
Texture analysis is one possible method to detect features in biomedical images. During texture analysis, texture related information is found by examining local variations in ima...
Brent Woods, Bradley D. Clymer, Joel H. Saltz, Tah...
IGARSS
2009
13 years 5 months ago
Reducing the Dimensionality of Hyperspectral Data using Diffusion Maps
We examine the analysis of hyperspectral data produced by the Hyperspectral Core Imager of AngloGold Ashanti. The dimension of the data is reduced using diffusion maps and the dat...
Luis du Plessis, Steven Damelin, Michael Sears
BMCBI
2010
243views more  BMCBI 2010»
13 years 7 months ago
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
Christoph Bartenhagen, Hans-Ulrich Klein, Christia...
KDD
2000
ACM
149views Data Mining» more  KDD 2000»
13 years 11 months ago
Efficient clustering of high-dimensional data sets with application to reference matching
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
Andrew McCallum, Kamal Nigam, Lyle H. Ungar