Disclosed by the present application are a text categorization model training method, apparatus, computer device, and storage medium, said method comprising: obtaining, from a preset sample library, first sample data having a category label and second sample data not having a category label; establishing a primary categorization model according to the first sample data; at the same time, calculating an information entropy value and a correlation value of the second sample data; according to a preset category labeling method, labeling the second sample data whose information entropy value and correlation value meet preset conditions to obtain third sample data; using the third sample data to train the primary categorization model to obtain an intermediate categorization model; using the first sample data and the third sample data to train the intermediate categorization model to obtain a text categorization model. The technical solution of the present application solves the problem, during text categorization model training, of the training sample size being enormous and the training time being long.
TEXT CATEGORIZATION MODEL TRAINING METHOD, APPARATUS, COMPUTER DEVICE, AND STORAGE MEDIUM