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» Clustering Improves the Exploration of Graph Mining Results
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PKDD
2005
Springer
122views Data Mining» more  PKDD 2005»
15 years 5 months ago
A Probabilistic Clustering-Projection Model for Discrete Data
For discrete co-occurrence data like documents and words, calculating optimal projections and clustering are two different but related tasks. The goal of projection is to find a ...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
CIKM
2010
Springer
14 years 10 months ago
Discovery of numerous specific topics via term co-occurrence analysis
We describe efficient techniques for construction of large term co-occurrence graphs, and investigate an application to the discovery of numerous fine-grained (specific) topics. A...
Omid Madani, Jiye Yu
DAWAK
2009
Springer
15 years 6 months ago
Dynamic Clustering-Based Estimation of Missing Values in Mixed Type Data
The appropriate choice of a method for imputation of missing data becomes especially important when the fraction of missing values is large and the data are of mixed type. The prop...
Vadim V. Ayuyev, Joseph Jupin, Philip W. Harris, Z...
SEMCO
2008
IEEE
15 years 6 months ago
SEMSOC: SEMantic, SOcial and Content-Based Clustering in Multimedia Collaborative Tagging Systems
A huge amount of data and metadata emerges from Web 2.0 applications which have transformed the Web to a mass social interaction and collaboration medium. Collaborative Tagging Sy...
Eirini Giannakidou, Ioannis Kompatsiaris, Athena V...
SDM
2007
SIAM
98views Data Mining» more  SDM 2007»
15 years 1 months ago
Lattice based Clustering of Temporal Gene-Expression Matrices
Individuals show different cell classes when they are in the different stages of a disease, have different disease subtypes, or have different response to a treatment or envir...
Yang Huang, Martin Farach-Colton