Pre-training model method for mathematical problem classification

The invention discloses a pre-training model method for mathematic problem classification, and the method comprises the following steps: constructing a knowledge graph of mathematic knowledge point relations, and generating a knowledge point vector for each knowledge point in the knowledge graph according to the relation between the knowledge points; generating text vectors according to mathematical problems in the training set and the verification set, importing the text vectors and knowledge point vectors and creating a text pre-training model, wherein the model comprises semantic mask language model training, related problem prediction model training and problem correlation sorting training; and importing the test set into a pre-training model, predicting the processed mathematical questions, and outputting a result. The knowledge graph is integrated, and a novel masking and prediction strategy is provided to enhance knowledge point representation, so that prediction effect is moreaccurate; the model uses