Bullet screen text classification method, device, equipment, and storage medium

Abstract

The invention provides a bullet screen text classification method, a bullet screen text classification device, equipment and a storage medium. The method comprises the steps: obtaining an imbalance training data set with a pre-marked category, and dividing the training data set into a sufficient sample and an insufficient sample; training the sufficient samples by adopting a textCNN model; carrying out model training on the insufficient samples by adopting an SVM classifier; inputting a text to be tested into the trained textCNN model, and outputting classification probabilities of various categories in sufficient samples; and if the output classification probability is smaller than a first preset threshold, inputting the to-be-tested text into a trained SVM classifier, and outputting a predicted category. According to the method, the classification models for different text scales are obtained through separate training according to the sizes of the training samples, then the two classification models are combined to be used for classifying the to-be-detected text, the problem of data imbalance of the training samples is solved, compared with single model training, the risk of over-fitting can be reduced, bias is reduced, and the recognition accuracy is higher.

Description

technical field [0001] The invention belongs to the technical field of big data, and in particular relates to a barrage text classification method, device, equipment and storage medium. Background technique [0002] On the live broadcast platform, gangsters will send a large number of advertising bullet screens or pornographic bullet screens in the live broadcast room to achieve the purpose of destroying the live broadcast environment of the platform and illegally seeking improper benefits, which not only greatly destroys the user experience, but also directly and indirectly Broke the interests of the platform and normal users. At present, the interception of spam barrage can be achieved by training text models, but when training spam barrage text classification models, typical "28 distribution" data is often encountered, and the distribution of training samples is uneven, resulting in ineffective classification models. For example, the model always divides the samples to b...

AI Technical Summary

Problems solved by technology

[0004] The present invention proposes a barrage text classification method, device, equipment and storage medium, which are used to solve the problem that the classification model is not effective due to unbalanced distribution of training samples when classifying live barrage texts

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