Document space dimension reduction by Latent Semantic Analysis and Hebbian neural network

This paper presents the comparison of the text document space dimension reduction and the text document clustering and also the keyword space dimension reduction and keyword clustering by the latent semantic analysis and by the Hebbian neural network with Oja learning rule. Results of this neural network are compared with the results of the latent semantic analysis which uses the Singular value decomposition for dimension space reduction of the text documents in natural language.