A Text Classification Algorithm for Telephone Appeal Based on DenseNet for Power Field

Abstract

The invention discloses a telephone appeal text classification algorithm based on DenseNet facing the electric power field, belonging to the technical field of text classification algorithms, through preprocessing the text to be classified, data augmentation, establishing a vocabulary dictionary, word vector id matching, and word vector reduction Dimensions, concatenated eigenvalues, and random permutations and combinations of concatenated eigenvalues ​​are used to obtain a text classifier, and the text classifier is used to classify text. The DenseNet-based phone appeal text classification algorithm for the electric power field provided by the present invention can effectively make up for the shortcomings of traditional algorithms, and can well adapt to the characteristics of strong professionalism, large length differences, and mixed characters and numbers in electric power appeal texts. On the premise of ensuring the classification accuracy, the complexity of the model is reduced, and the rapid and accurate classification of the telephone appeal text in the electric power field is realized, which satisfies the classification requirements well.

Description

technical field [0001] The invention relates to the technical field of text classification algorithms, in particular to a text classification algorithm for telephone appeals based on DenseNet facing the electric power field. Background technique [0002] With the popularization and improvement of power grid construction, there are more and more grid users. In order to ensure the stability of power grid power supply and improve the satisfaction of users with electricity, the power grid company has built a telephone feedback platform, and users can consult the service content through the telephone feedback platform. , Reflecting power failures, making evaluations on the grid company, making comments or complaints to the grid company, etc. In order to better improve the construction and service of power grid companies through the telephone feedback platform, it is necessary to classify the text of telephone appeals. Existing classification methods generally classify texts thro...

AI Technical Summary

Problems solved by technology

However, this method will deepen the network level, requires a huge amount of parameters to be trained, and is sensitive to the sparsity of text features, and the classification speed is slow, which cannot well meet the requirements of classifying telephone appeal texts in the power field.

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