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With the development of electronic periodicals, it is unavoidable that there are some classification management problems. But currently the classification management of papers basically majors in manual classification. Based on Chinese medical literature, this essay compares and analyzes these automatic classification algorithms: support vector machine (SVM), BP neural network, and random forest. It is found that SVM is more suitable for automatic classification of Chinese medical literature.

Comparative Research on Automatic Classification Algorithms Based on Chinese Medical Literature