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SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
16 years 3 months 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
WSDM
2012
ACM
329views Data Mining» more  WSDM 2012»
14 years 1 months ago
Beyond 100 million entities: large-scale blocking-based resolution for heterogeneous data
A prerequisite for leveraging the vast amount of data available on the Web is Entity Resolution, i.e., the process of identifying and linking data that describe the same real-worl...
George Papadakis, Ekaterini Ioannou, Claudia Niede...
KDD
2010
ACM
279views Data Mining» more  KDD 2010»
15 years 10 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 6 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 7 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...