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77
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ICPR
2006
IEEE
16 years 3 months ago
A Prototypes-Embedded Genetic K-means Algorithm
This paper presents a genetic algorithm (GA) for Kmeans clustering. Instead of the widely applied stringof-group-numbers encoding, we encode the prototypes of the clusters into th...
Hsin-Chia Fu, Hsin-Min Wang, Shih-Sian Cheng, Yi-H...
CIT
2007
Springer
15 years 8 months ago
Performance Assessment of Some Clustering Algorithms Based on a Fuzzy Granulation-Degranulation Criterion
In this paper a fuzzy quantization dequantization criterion is used to propose an evaluation technique to determine the appropriate clustering algorithm suitable for a particular ...
Sriparna Saha, Sanghamitra Bandyopadhyay
GECCO
2010
Springer
338views Optimization» more  GECCO 2010»
15 years 28 days ago
Multiobjective evolutionary community detection for dynamic networks
A multiobjective genetic algorithm for detecting communities in dynamic networks, i.e., networks that evolve over time, is proposed. The approach leverages on the concept of evolu...
Francesco Folino, Clara Pizzuti
107
Voted
DIS
2006
Springer
15 years 6 months ago
A Novel Framework for Discovering Robust Cluster Results
We propose a novel method, called heterogeneous clustering ensemble (HCE), to generate robust clustering results that combine multiple partitions (clusters) derived from various cl...
Hye-Sung Yoon, Sang-Ho Lee, Sung-Bum Cho, Ju Han K...
141
Voted
TSMC
2008
189views more  TSMC 2008»
15 years 2 months ago
Automatic Clustering Using an Improved Differential Evolution Algorithm
Differential evolution (DE) has emerged as one of the fast, robust, and efficient global search heuristics of current interest. This paper describes an application of DE to the aut...
Swagatam Das, Ajith Abraham, Amit Konar