Document Space Dimension Reduction by Latent Semantic Analysis and Hebbian Neural Network

被引：0

作者：

Mokris, I. ^{[1
]}

Skovajsova, L. ^{[1
]}

机构：

[1] Slovak Acad Sci, Inst Informat, Bratislava 84507, Slovakia

来源：

2008 6TH INTERNATIONAL SYMPOSIUM ON INTELLIGENT SYSTEMS AND INFORMATICS | 2008年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：60 / 63

页数：4

共 20 条

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