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PAKDD
2007
ACM
143views Data Mining» more  PAKDD 2007»
15 years 11 months ago
Clustering Ensembles Based on Normalized Edges
The co-association (CA) matrix was previously introduced to combine multiple partitions. In this paper, we analyze the CA matrix, and address its difference from the similarity ma...
Yan Li, Jian Yu, Pengwei Hao, Zhulin Li
ICDM
2003
IEEE
138views Data Mining» more  ICDM 2003»
15 years 10 months ago
Ontologies Improve Text Document Clustering
Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large sets of documents into a small number of meaningful ...
Andreas Hotho, Steffen Staab, Gerd Stumme
138
Voted
ICANN
2009
Springer
15 years 9 months ago
A Two Stage Clustering Method Combining Self-Organizing Maps and Ant K-Means
This paper proposes a clustering method SOMAK, which is composed by Self-Organizing Maps (SOM) followed by the Ant K-means (AK) algorithm. The aim of this method is not to find an...
Jefferson R. Souza, Teresa Bernarda Ludermir, Lean...
BIBE
2004
IEEE
120views Bioinformatics» more  BIBE 2004»
15 years 8 months ago
Identifying Projected Clusters from Gene Expression Profiles
In microarray gene expression data, clusters may hide in subspaces. Traditional clustering algorithms that make use of similarity measurements in the full input space may fail to ...
Kevin Y. Yip, David W. Cheung, Michael K. Ng, Kei-...
ICPR
2010
IEEE
15 years 8 months ago
Cluster-Pairwise Discriminant Analysis
Pattern recognition problems often suffer from the larger intra-class variation due to situation variations such as pose, walking speed, and clothing variations in gait recognition...
Yasushi Makihara, Yasushi Yagi