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SDM
2011
SIAM
243views Data Mining» more  SDM 2011»
14 years 7 months ago
Data Integration via Constrained Clustering: An Application to Enzyme Clustering
When multiple data sources are available for clustering, an a priori data integration process is usually required. This process may be costly and may not lead to good clusterings,...
Elisa Boari de Lima, Raquel Cardoso de Melo Minard...
132
Voted
KDD
2010
ACM
279views Data Mining» more  KDD 2010»
15 years 8 months ago
Unifying dependent clustering and disparate clustering for non-homogeneous data
Modern data mining settings involve a combination of attributevalued descriptors over entities as well as specified relationships between these entities. We present an approach t...
M. Shahriar Hossain, Satish Tadepalli, Layne T. Wa...
156
Voted
BMCBI
2006
126views more  BMCBI 2006»
15 years 5 months ago
Effect of data normalization on fuzzy clustering of DNA microarray data
Background: Microarray technology has made it possible to simultaneously measure the expression levels of large numbers of genes in a short time. Gene expression data is informati...
Seo Young Kim, Jae Won Lee, Jong Sung Bae
SDM
2007
SIAM
112views Data Mining» more  SDM 2007»
15 years 6 months ago
PoClustering: Lossless Clustering of Dissimilarity Data
Given a set of objects V with a dissimilarity measure between pairs of objects in V , a PoCluster is a collection of sets P ⊂ powerset(V ) partially ordered by the ⊂ relation ...
Jinze Liu, Qi Zhang, Wei Wang 0010, Leonard McMill...
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
16 years 5 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui