Text classification method and device

Abstract

The invention discloses a text classification method, which is used for realizing text classification, simplifying classification operation and improving the text classification accuracy. The method comprises the following steps of: segmenting the obtained text contents to obtain a plurality of words; determining a word vector of a word in a spherical space model for each word in the plurality of words, wherein the word vector of the word comprises a normalized word frequency value which is normalized by a word frequency value of the word on each category, the spherical space model is a multi-dimensional spherical model which takes unit length as a radius, the dimensionality of the spherical space is equal to the number of the categories, and the category corresponds to a category vector in the spherical space; determining a distance from the sum of the word vectors of the plurality of words to the category vector of the category for each category; and introducing the text into a category corresponding to the shortest distance. The invention also discloses a device for implementing the method.

Description

technical field [0001] The present application relates to the field of computer and communication, in particular to a method and device for text classification. Background technique [0002] Text classification is an important content of text mining, which refers to determining a category for each document in a document collection according to a predefined subject category. Classifying documents through an automatic text classification system can help people better find the information and knowledge they need. Classification is seen as the most basic form of cognition of information. The traditional literature classification research has rich research results and a considerable practical level. However, with the rapid growth of text information, especially the surge of online text information on the Internet, automatic text classification has become a key technology for processing and organizing large amounts of document data. Now, text classification is widely used in va...

AI Technical Summary

Problems solved by technology

[0004] In the prior art, it is necessary to calculate the similarity between each text vector and all the feature vectors of the candidate category. Each calculation needs to be measured by the cosine of the included angle. The calculation amount is very large, and the existing technology does not have any constraints on the semantics of the text. The classification accuracy is not very good

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