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SSDBM
2008
IEEE
114views Database» more  SSDBM 2008»
14 years 2 months ago
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
Hans-Peter Kriegel, Peer Kröger, Erich Schube...
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 8 months ago
A highly-usable projected clustering algorithm for gene expression profiles
Projected clustering has become a hot research topic due to its ability to cluster high-dimensional data. However, most existing projected clustering algorithms depend on some cri...
Kevin Y. Yip, David W. Cheung, Michael K. Ng
ICDE
2012
IEEE
309views Database» more  ICDE 2012»
11 years 10 months ago
Evaluation of Clusterings - Metrics and Visual Support
—When comparing clustering results, any evaluation metric breaks down the available information to a single number. However, a lot of evaluation metrics are around, that are not ...
Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel...
GECCO
2003
Springer
153views Optimization» more  GECCO 2003»
14 years 1 months ago
PalmPrints: A Novel Co-evolutionary Algorithm for Clustering Finger Images
The purpose of this study is to explore an alternative means of hand image classification, one that requires minimal human intervention. The main tool for accomplishing this is a G...
Nawwaf N. Kharma, Ching Y. Suen, Pei F. Guo
EUROPAR
2001
Springer
14 years 12 days ago
Self-Organizing Hierarchical Cluster Timestamps
Distributed-system observation tools require an efficient data structure to store and query the partial-order of execution. Such data structures typically use vector timestamps to...
Paul A. S. Ward, David J. Taylor