Identification and Prediction of Key Technologies in Ginsenosides Based on Genetic Knowledge Persistence Algorithm

Abstract

Objective To study the key technologies in the field of ginsenosides and to offer a guide for the future development ginsenosides through the main path identification method based on genetic knowledge persistence algorithm (GKPA). Methods The global ginsenoside invention authorized patents were used as the data source to construct a ginsenoside patent self-citation network, and to identify high knowledge persistent patents (HKPP) of ginsenoside technology based on the GKPA, and extract its high knowledge persistence main path (HKPMP). Finally, the genetic forward and backward path (GFBP) was used to search the nodes on the main path, and draw the genetic forward and backward main path (GFBMP) of ginsenoside technology. Results and Conclusion The algorithm was applied to the field of ginsenosides. The research results show the milestone patents in ginsenosides technology and the main evolution process of three key technologies, which points out the future direction for the technological development of ginsenosides. The results obtained by this algorithm are more interpretable, comprehensive and scientific.

Keywords

ginsenoside / genetic knowledge persistence algorithm (GKPA) / high knowledge persistence patent (HKPP) / genetic forward and backward path (GFBP) / main path analysis