Name
Abstract | ||
|---|---|---|
A modified variable string length genetic algorithm, called MVGA, is proposed for text clustering in this paper. Our algorithm has been exploited for automatically evolving the optimal number of clusters as well as providing proper data set clustering. The chromosome is encoded by special indices to indicate the location of each gene. More effective version of evolutional steps can automatically adjust the influence between the diversity of the population and selective pressure during generations. The superiority of the MVGA over conventional variable string length genetic algorithm (VGA) is demonstrated by providing proper text clustering. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11881070_103 | ICNC (1) |
Keywords | Field | DocType |
selective pressure,genetic algorithm-based text,genetic algorithm,effective version,optimal number,modified variable string length,special index,proper data,proper text clustering,evolutional step,conventional variable string length,text clustering | Fuzzy clustering,Canopy clustering algorithm,CURE data clustering algorithm,Data stream clustering,Correlation clustering,Affinity propagation,Computer science,Determining the number of clusters in a data set,Algorithm,Cluster analysis | Conference |
Volume | ISSN | ISBN |
4221 | 0302-9743 | 3-540-45901-4 |
Citations | PageRank | References |
18 | 1.10 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Song | 1 | 113 | 15.51 |
| Soon Cheol Park | 2 | 197 | 14.78 |