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ISDA
2006
IEEE
14 years 1 months ago
Finding Groups in Data: Cluster Analysis with Ants
We present in this paper a modification of Lumer and Faieta’s algorithm for data clustering. This algorithm discovers automatically clusters in numerical data without prior kno...
Urszula Boryczka
TKDE
2008
111views more  TKDE 2008»
13 years 7 months ago
A Point Symmetry-Based Clustering Technique for Automatic Evolution of Clusters
In this paper, a new symmetry-based genetic clustering algorithm is proposed which automatically evolves the number of clusters as well as the proper partitioning from a data set. ...
Sanghamitra Bandyopadhyay, Sriparna Saha
FLAIRS
2007
13 years 9 months ago
Improving Cluster Method Quality by Validity Indices
Clustering attempts to discover significant groups present in a data set. It is an unsupervised process. It is difficult to define when a clustering result is acceptable. Thus,...
Narjes Hachani, Habib Ounelli
ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
14 years 1 months ago
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
This paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. In this paper, based on the rece...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...
GECCO
2007
Springer
209views Optimization» more  GECCO 2007»
14 years 1 months ago
Kernel based automatic clustering using modified particle swarm optimization algorithm
This paper introduces a method for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring clusters. The proposed ...
Ajith Abraham, Swagatam Das, Amit Konar