Abstract

Deep learning technology has been rapidly developed in recent years and has been increasingly applied in the field of text classification, and many effective and novel classification methods have emerged. The development history of text classification is introduced, the text classification problem based on deep neural networks is analyzed, the characteristics and performance of various classical classification methods are compared and summarized, and it is shown that deep neural networks are more advantageous than traditional machine learning methods in the field of text classification on the whole. The shortcomings of current deep text classification models are pointed out and future research directions prospect.

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