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PKDD
2000
Springer
144views Data Mining» more  PKDD 2000»
15 years 10 months ago
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Markus M. Breunig, Hans-Peter Kriegel, Jörg S...
BMCBI
2008
143views more  BMCBI 2008»
15 years 6 months ago
Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering
Background: The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, ...
Shibu Yooseph, Weizhong Li, Granger G. Sutton
KDD
2007
ACM
220views Data Mining» more  KDD 2007»
16 years 6 months ago
SCAN: a structural clustering algorithm for networks
Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...
SDM
2009
SIAM
176views Data Mining» more  SDM 2009»
16 years 3 months ago
Constraint-Based Subspace Clustering.
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
Élisa Fromont, Adriana Prado, Céline...
ALENEX
2008
142views Algorithms» more  ALENEX 2008»
15 years 8 months ago
Consensus Clustering Algorithms: Comparison and Refinement
Consensus clustering is the problem of reconciling clustering information about the same data set coming from different sources or from different runs of the same algorithm. Cast ...
Andrey Goder, Vladimir Filkov