Informative text filter method and system

Abstract

The invention relates to an informative text filter method and system. The informative text filter method comprises the steps that informative text to be audited is preprocessed, and multiple corresponding terms are obtained; a semantic extension parameter table is called in, and the informative text to be audited is mapped to a determined theme space from a term space according to the terms and the semantic extension parameter table; classifier parameters are called in, statistical semantic analysis is conducted on the informative text to be audited according to the classifier parameters, and corresponding classification labels are given and stored into a training sample library. According to the informative text filter method and system, the classification labels corresponding to the informative text to be audited can be obtained by conducting preprocessing, mapping to the theme space from the term space and statistical semantic analysis on the informative text to be audited, the classification labels are stored into the training sample library together with the informative text to be audited after being obtained, an audited training set is automatically expanded, fast self-adaptive learning of training samples is achieved, and thus the practicability and the recognition accuracy of informative text filter are improved.

Description

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AI Technical Summary

Problems solved by technology

[0004] However, in reality, the existing content filtering devices are difficult to quickly and effectively build a training sample library, and cannot quickly converge adaptive learning in

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