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SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
16 years 9 days ago
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Fei Wang, Chris H. Q. Ding, Tao Li
SDM
2011
SIAM
243views Data Mining» more  SDM 2011»
14 years 6 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...
KDD
2010
ACM
279views Data Mining» more  KDD 2010»
15 years 7 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...
BMCBI
2006
126views more  BMCBI 2006»
15 years 3 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 4 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...