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A new unsupervised feature selection method for text clustering based on genetic algorithms

โœ Scribed by Pirooz Shamsinejadbabki, Mohammad Saraee


Book ID
113069660
Publisher
Springer US
Year
2011
Tongue
English
Weight
584 KB
Volume
38
Category
Article
ISSN
0925-9902

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## a b s t r a c t In this paper, we develop a genetic algorithm method based on a latent semantic model (GAL) for text clustering. The main difficulty in the application of genetic algorithms (GAs) for document clustering is thousands or even tens of thousands of dimensions in feature space which