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ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
16 years 1 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
NAS
2007
IEEE
16 years 1 months ago
Performance Evaluation of A Load Self-Balancing Method for Heterogeneous Metadata Server Cluster Using Trace-Driven and Syntheti
In cluster-based storage systems, the metadata server cluster must be able to adaptively distribute responsibility for metadata to maintain high system performance and long-term l...
Bin Cai, Changsheng Xie, Guangxi Zhu
PAKDD
2007
ACM
152views Data Mining» more  PAKDD 2007»
16 years 25 days ago
Spectral Clustering Based Null Space Linear Discriminant Analysis (SNLDA)
While null space based linear discriminant analysis (NLDA) obtains a good discriminant performance, the ability easily suffers from an implicit assumption of Gaussian model with sa...
Wenxin Yang, Junping Zhang
ICDM
2005
IEEE
148views Data Mining» more  ICDM 2005»
16 years 9 days ago
Online Hierarchical Clustering in a Data Warehouse Environment
Many important industrial applications rely on data mining methods to uncover patterns and trends in large data warehouse environments. Since a data warehouse is typically updated...
Elke Achtert, Christian Böhm, Hans-Peter Krie...
ACMSE
2004
ACM
16 years 4 days ago
Topic-based clustering of news articles
Recent years have witnessed an explosion in the availability of news articles on the World Wide Web. Although searchengines’ algorithms have made it easier to locate these docum...
Najaf Ali Shah, Ehab M. ElBahesh