TEXT SENTIMENT ANALYSIS MODEL TRAINING METHOD, APPARATUS AND DEVICE, AND READABLE STORAGE MEDIUM

摘要

A text sentiment analysis model training method, apparatus and device, and a readable storage medium, relating to the technical field of artificial intelligence. The method comprises: obtaining a text sample to be trained (S10); performing word segmentation processing on the text sample by means of a preset word segmentation method, and dividing the text sample into a plurality of different words (S20); performing encoding processing on the plurality of different words on the basis of a preset encoding method to obtain word vectors (S30); inputting the word vectors into a preset deep neural network, and performing dimension reduction processing on the word vectors on the basis of an embedded layer (S40); calculating word vectors after dimension reduction on the basis of a hidden layer in the deep neural network to obtain corresponding features (S50); classifying the features corresponding to the text sample by means of a multi-classification SVM support vector machine, and determining a sentiment category (S60); and determining a difference value between the sentiment category and a correct sentiment category on the basis of a loss function, and when the difference value satisfies a preset condition, determining that training of a text sentiment analysis model is completed (S70). The method improves the accuracy of text sentiment analysis.