Automatic document classification based on latent semantic analysis

被引：2

作者：

Kuralenok, I ^{[1
]}

Nekrest'yanov, I ^{[1
]}

机构：

[1] St Petersburg State Univ, St Petersburg 199164, Russia

来源：

PROGRAMMING AND COMPUTER SOFTWARE | 2000年 / 26卷 / 04期

关键词：

Latent Semantic Analysis; Latent Semantic Indexing; Hypothesis Space; Topic Description; Semantic Proximity;

D O I：

10.1007/BF02759469

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In this paper, the problem of automatic document classification by a set of given topics is considered. The method proposed is based on the use of the latent semantic analysis to retrieve semantic dependencies between words. The classification of documents is based on these dependencies. The results of experiments performed on the basis of the standard test data set TREC (Text REtrieval Conference) confirm the attractiveness of this approach. The relatively low computational complexity of this method at the classification stage makes it possible to be applied to the classification of document streams.

引用

页码：199 / 206

页数：8

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