Design of Deep Learning Mixed Language Short Text Sentiment Classification System Based on CNN Algorithm
Wang Wang, Guangze Wen, Zikun Zheng
Abstract
Deep learning began to emerge in the 1990s, and with the development and updating of networks, higher requirements were placed on data set analysis techniques. Firstly, it elaborates on the classification algorithm based on deep learning, which includes a multi-layer perceptron model, a recurrent neural network model and an attention mechanism model. Secondly, this paper studies the model construction and sentiment analysis based on BL_CNN, gives the mathematical model and training algorithm of deep learning, and then analyzes the dataset based on CNN, and gives the neural network structure diagram. Finally, the design of the short text sentiment classification system based on CNN is studied, and the regression model and emotion statistical clustering algorithm based on deep learning are proposed, and the method is used to predict short text data.