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139
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SDM
2004
SIAM
141views Data Mining» more  SDM 2004»
15 years 4 months ago
Visually Mining through Cluster Hierarchies
Similarity search in database systems is becoming an increasingly important task in modern application domains such as multimedia, molecular biology, medical imaging, computer aid...
Stefan Brecheisen, Hans-Peter Kriegel, Peer Kr&oum...
149
Voted
IJKDB
2010
170views more  IJKDB 2010»
15 years 24 days ago
Clustering Genes Using Heterogeneous Data Sources
Clustering of gene expression data is a standard exploratory technique used to identify closely related genes. Many other sources of data are also likely to be of great assistance...
Erliang Zeng, Chengyong Yang, Tao Li, Giri Narasim...
116
Voted
ADC
2006
Springer
120views Database» more  ADC 2006»
15 years 9 months ago
Approximate data mining in very large relational data
In this paper we discuss eNERF, an extended version of non-Euclidean relational fuzzy c-means (NERFCM) for approximate clustering in very large (unloadable) relational data. The e...
James C. Bezdek, Richard J. Hathaway, Christopher ...
166
Voted
BMCBI
2010
171views more  BMCBI 2010»
15 years 3 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
118
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NIPS
1997
15 years 4 months ago
Active Data Clustering
Active data clustering is a novel technique for clustering of proximity data which utilizes principles from sequential experiment design in order to interleave data generation and...
Thomas Hofmann, Joachim M. Buhmann