Feature extraction method for text categorization based on improved mutual information and entropy

Abstract

The invention provides a feature extraction method for text categorization. The feature extraction method is used for solving the problem that the accuracy rate and the recall rate of text categorization need to be increased further. The feature extraction method is a strategic method. In consideration of the concept of entropy in statistical thermodynamics, entropy is used for describing the degree of disorder of a system and is significantly applied to the fields of cybernetics, probability theory, number theory, astrophysics, bioscience, information theory and the like. According to the feature extraction method, entropy can also be used in text categorization, a feature is regarded as an event, a category set of text is a system, and therefore entropy can be used for measuring the degree of disorder of features and categories and converted into the closeness degree of the relation between the features and the categories. According to the feature extraction method, on the basis of improved mutual information, the concept of entropy is combined, a new feature evaluation function is provided, feature extraction is conducted on the basis of the function, a superior feature subset can be selected for showing the text and building a categorizer, and therefore the accuracy rate and the recall rate of text categorization are increased.

Description

technical field [0001] The invention relates to the technical field of text mining, in particular to a text classification feature extraction method based on improved mutual information and entropy. Background technique [0002] With the development of computer technology and the popularization of the Internet, we are in an information age, and the number of online texts is increasing rapidly. The previous method of manually screening texts for classification is no longer suitable, and there is an urgent need for a fast and efficient The technology of collecting data and organizing the required information, thus producing text classification technology. Text classification refers to the process of classifying texts into corresponding predefined categories according to their content under a given classification system. The process of text classification is actually to identify the pattern features of the text, and the key technologies include text preprocessing, feature extr...

AI Technical Summary

Problems solved by technology

[0014] The purpose of the present invention is to provide a text classification feature extraction method based on improved mutual information and entropy, which is used to solve the problem that the accuracy and recall rate of text classification need to be further improved

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