Research on Link Prediction Based on Compatibility of Chinese Medicinal Materials

Abstract

Link prediction is a network analysis method to solve practical problems and has important research value in many fields. In the field of traditional Chinese medicine, according to the different needs of the disease and the different characteristics of the drugs, the combination of the two drugs is called drug pairing. Based on traditional Chinese medicine network, this study provides a new research perspective based on complex network and link prediction. Aiming at the problem of strong randomness in the traditional random walk, a new link prediction method based on graph embedding method is proposed in this paper. Compared with the traditional random walk, the index proposed in this paper improves the performance greatly. Through link prediction, it is verified that the drug pair without compatibility in the existing prescription may appear in the future prescription, as a supplement to the new drug pair.