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IBPRIA
2003
Springer
15 years 11 months ago
Incrementally Assessing Cluster Tendencies with a Maximum Variance Cluster Algorithm
A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
Krzysztof Rzadca, Francesc J. Ferri
NCA
2007
IEEE
16 years 15 days ago
Discovering Web Workload Characteristics through Cluster Analysis
In this paper we present clustering analysis of sessionbased Web workloads of eight Web servers using the intrasession characteristics (i.e., number of requests per session, sessi...
Fengbin Li, Katerina Goseva-Popstojanova, Arun Ros...
EDBT
2009
ACM
302views Database» more  EDBT 2009»
16 years 1 months ago
RankClus: integrating clustering with ranking for heterogeneous information network analysis
As information networks become ubiquitous, extracting knowledge from information networks has become an important task. Both ranking and clustering can provide overall views on in...
Yizhou Sun, Jiawei Han, Peixiang Zhao, Zhijun Yin,...
127
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CSB
2003
IEEE
135views Bioinformatics» more  CSB 2003»
15 years 11 months ago
Clustering Binary Fingerprint Vectors with Missing Values for DNA Array Data Analysis
Andres Figueroa, James Borneman, Tao Jiang
AAI
2011
275views Algorithms» more  AAI 2011»
15 years 1 months ago
K-attractors: a Partitional Clustering Algorithm for Numeric Data Analysis
Yiannis Kanellopoulos, Panagiotis Antonellis, Chri...