Method for classifying texts on basis of nave Bayes

Abstract

The invention discloses a method for classifying texts on the basis of nave Bayes. The method includes steps of 1, forming feature vectors of the to-be-classified texts by the aid of word segmentation tools, comparing the feature vectors to common words, removing meaningless words in the to-be-classified texts and setting weights w for each word s which appears in the to-be-classified texts; 2, acquiring probability sets Q (w<1>, ..., w<n>) of P (w<1>, ..., w<n>) which appear in training text sets D, and multiplying attributes in the Q (w<1>, ..., w<n>) to obtain prior probability P (w|D) of the P (w<1>, ..., w<n>) which appear in the training text sets D; 3, dividing the quantities of files in the training text sets D by the total number of integral training text sets to obtain prior probability P (D), multiplexing the P (D) by P (x|D) to obtain posterior probability P (D|w) of the P (w<1>, ..., w<n>) in the training text sets D; 4, repeatedly carrying out the steps 2 and 3 and computing all posterior probability; 5, comparing results obtained at the step 4 to obtain the maximum posterior probability P (D). The P (w<1>, ..., w<n>) belong to D categories. The method has the advantages that the method is good in performance and has excellent practical application values in classifying appeal texts of electric power users.

Description

technical field [0001] The invention relates to the field of railway catenary detection, in particular to a text classification method based on naive Bayesian. Background technique [0002] The power customer service department has to face a large number of user appeal information every day. In the traditional mode, the operator classifies the user's appeal information through subjective judgment, and then delivers it to the corresponding department for processing. This method requires manual checking and confirmation one by one, and the informatization and intelligence are seriously insufficient. [0003] The content of text classification of power user appeals is very rich, and these contents are often found in various international conferences and related journals or magazines such as information retrieval, machine learning, knowledge mining and discovery, pattern recognition, smart grid, power science and application, etc. Representative review articles include "Machin...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a text classification method based on naive Bayesian, which solves the technical problem that the existing text classification algorithm is not ideal. Assuming this deficiency independently, the performance of the method is better, and it has a good practical application value in the power user appeal text classification problem

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