BERT fusion capsule network elevator fault complaint text classification method
A text classification and fault type technology, applied in neural learning methods, biological neural network models, semantic analysis, etc., can solve problems such as the lack of long-distance dependencies of encoded texts, achieve the effect of improving classification efficiency and reducing sentence vector dimensions
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[0036] The present invention will be further described below with reference to the accompanying drawings and implementation cases.
[0037] figure 2 The network structure of the BERT-CapsNet complaint text classification model constructed by the present invention is shown. The input of the model is the processed complaint text, which is encoded by the embedding layer and then input to Bert's bidirectional Transformer. The vector corresponding to each Token is used as the output (a vector with a dimension of 768), which is input to the linear layer and activated by the Tanh function to generate the final sentence vector. The linear layer is mainly to reduce the dimension of the sentence vector, thereby reducing the calculation of subsequent text classification. complexity and improve the efficiency of text classification. The Reshape layer changes the shape of the sentence vector to make it suitable for input into the downstream capsule network for text classification. The ca...
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