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WCRE
2010
IEEE
13 years 8 months ago
Evaluating the Impact of Software Evolution on Software Clustering
—The evolution of a software project is a rich data source for analyzing and improving the software development process. Recently, several research groups have tried to cluster s...
Fabian Beck, Stephan Diehl
KDD
2010
ACM
326views Data Mining» more  KDD 2010»
13 years 8 months ago
Document clustering via dirichlet process mixture model with feature selection
One essential issue of document clustering is to estimate the appropriate number of clusters for a document collection to which documents should be partitioned. In this paper, we ...
Guan Yu, Ruizhang Huang, Zhaojun Wang
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 10 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
VTC
2006
IEEE
129views Communications» more  VTC 2006»
14 years 4 months ago
A Framework for Automatic Clustering of Parametric MIMO Channel Data Including Path Powers
— We present a solution to the problem of identifying clusters from MIMO measurement data in a data window, with a minimum of user interaction. Conventionally, visual inspection ...
Nicolai Czink, Pierluigi Cera, Jari Salo, Ernst Bo...
SSDBM
2005
IEEE
218views Database» more  SSDBM 2005»
14 years 3 months ago
The "Best K" for Entropy-based Categorical Data Clustering
With the growing demand on cluster analysis for categorical data, a handful of categorical clustering algorithms have been developed. Surprisingly, to our knowledge, none has sati...
Keke Chen, Ling Liu