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JCP
2007
149views more  JCP 2007»
15 years 1 months ago
Partitional Clustering Techniques for Multi-Spectral Image Segmentation
Abstract— Analyzing unknown data sets such as multispectral images often requires unsupervised techniques. Data clustering is a well known and widely used approach in such cases....
Danielle Nuzillard, Cosmin Lazar
BMCBI
2008
142views more  BMCBI 2008»
15 years 1 months ago
Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...
KDD
2006
ACM
173views Data Mining» more  KDD 2006»
16 years 2 months ago
Robust information-theoretic clustering
How do we find a natural clustering of a real world point set, which contains an unknown number of clusters with different shapes, and which may be contaminated by noise? Most clu...
Christian Böhm, Christos Faloutsos, Claudia P...
108
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PAKDD
2009
ACM
123views Data Mining» more  PAKDD 2009»
15 years 6 months ago
Clustering with Lower Bound on Similarity
We propose a new method, called SimClus, for clustering with lower bound on similarity. Instead of accepting k the number of clusters to find, the alternative similarity-based app...
Mohammad Al Hasan, Saeed Salem, Benjarath Pupacdi,...
PAKDD
2000
ACM
124views Data Mining» more  PAKDD 2000»
15 years 5 months ago
Feature Selection for Clustering
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
Manoranjan Dash, Huan Liu