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ICDM
2007
IEEE
140views Data Mining» more  ICDM 2007»
14 years 2 months ago
Finding Cohesive Clusters for Analyzing Knowledge Communities
Documents and authors can be clustered into “knowledge communities” based on the overlap in the papers they cite. We introduce a new clustering algorithm, Streemer, which fin...
Vasileios Kandylas, S. Phineas Upham, Lyle H. Unga...
TKDE
2008
127views more  TKDE 2008»
13 years 8 months ago
Maximal Subspace Coregulated Gene Clustering
Clustering is a popular technique for analyzing microarray data sets, with n genes and m experimental conditions. As explored by biologists, there is a real need to identify coregu...
Yuhai Zhao, Jeffrey Xu Yu, Guoren Wang, Lei Chen 0...
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
14 years 8 months ago
Dynamic hybrid clustering of bioinformatics by incorporating text mining and citation analysis
To unravel the concept structure and dynamics of the bioinformatics field, we analyze a set of 7401 publications from the Web of Science and MEDLINE databases, publication years 1...
Bart De Moor, Frizo A. L. Janssens, Wolfgang Gl&au...
JIIS
2006
103views more  JIIS 2006»
13 years 8 months ago
Time-focused clustering of trajectories of moving objects
Spatio-temporal, geo-referenced datasets are growing rapidly, and will be more in the near future, due to both technological and social/commercial reasons. From the data mining vie...
Mirco Nanni, Dino Pedreschi
SIGIR
2002
ACM
13 years 8 months ago
Unsupervised document classification using sequential information maximization
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
Noam Slonim, Nir Friedman, Naftali Tishby