Abstract:

Text classification is very important to text data mining and value exploration.The traditional text classification system has problems of weak feature extraction ability and low classification accuracy.Compared with the traditional text classification technology,deep learning technology has many advantages such as high accuracy and effective feature extraction.Therefore,it is necessary to apply deep learning technology to the text classification system to solve the problems of the traditional text classification system.The traditional text classification system was analyzed,and the architecture and key technologies of text classification system based on deep learning were proposed.Finally,several classification models were verified and compared,including the traditional classification model,TextCNN and CNN+LSTM.

Key words: deep learning, text classification, classification model, neural network