Method for automatically classifying text documents by utilizing body

Abstract

The invention relates to a method for automatically classifying text documents by utilizing a body, comprising the following steps: firstly expressing the characteristic information of a text document by utilizing a weighted key word set; and then expressing the characteristic information of a classifying catalogue by a body which is subject to body disambiguation and body expansion; transforming the body into a weighted word meaning set through analyzing the body structural characteristic; finally calculating the semantic similar value between the key word set of the text document and the body weighted word meaning set by utilizing a Earth Mover's Distance method; further calculating the similar value between the text document and the classifying catalogue; and classifying and sequencing the text document according to the similar value between the text document and the classifying catalogue. By utilizing the method of the invention, the text document can be automatically classified, and the accuracy of the text document classification can be improved.

Description

technical field [0001] The invention relates to a method for automatically classifying text documents by using an ontology, and belongs to the fields of computer information processing, information retrieval and the like. It is suitable for fast and accurate automatic classification of massive network text documents. Background technique [0002] In order to improve the efficiency of text document organization and better support users to browse and find information, text document classification has always been the focus of attention. At first, text document classification was done manually, but with more and more text document resources, manual classification has become impossible, so automatic text document classification technology has become the focus of research. [0003] Text document classification is generally divided into three stages: first, the feature information of the text document and the classification directory is extracted; then, the classifier calculates t...

AI Technical Summary

Problems solved by technology

[0005] 1) The traditional machine learning method to train the classifier needs to manually collect a large number of classified text document sets, which is very cumbersome, and for different classification categories, it is necessary to manually collect different text document sets to train the classifier;

[0006] 2) Traditional machine learning methods do not consider the semantic relationship between words, so it is difficult to improve the accuracy of classification

Images