Analysis of Text Classification Algorithm Based on Deep Learning
This paper expounds the construction of a CNN-LSTM hybrid model,which extracts text keyword features through CNN and learns semantic dependency relationships through LSTM.Compared with traditional SVM and BiLSTM models,this hybrid model achieves higher classification accuracy.The experimental results indicate that the CNN-LSTM model can achieve accurate text classification.
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