Analysis of research hot spots and evolutionary trends of traditional chinese medicine industry based on clustering algorithm

Based on TF-IDF and Kleinberg algorithm, this paper analyzes the clustering and time-zone mapping of related literature on China Knowledge Network (CNKI) from 2019 to 2024, identifies high-frequency keywords and emergent words, and analyzes the stage-by-stage evolution characteristics of research hotspots. It is found that the research hotspots focus on four major directions - TCM cultural inheritance and rural revitalization synergistic path, “Belt and Road” internationalization strategy layout, ecological cultivation of local medicinal herbs and regional branding, and Guangdong-Hong Kong-Macao Greater Bay Area institutional innovation and complex talent cultivation. The evolution trend shows a shift from policy-driven to a more comprehensive approach. The evolution trend shows a two-stage leap from policy-driven to technology-enabled, with intelligent diagnosis and treatment and global competitiveness assessment becoming the core issues at a later stage. Insufficient cross-institutional collaboration and weak industry-university-research synergy are the main bottlenecks in the transformation of results. It is suggested to promote industrial upgrading through mutual recognition of international standards, application of blockchain technology and training of complex talents. Future research can optimize the trend prediction by combining the complex network model, deepen the mechanism of TCM in the prevention and control of chronic diseases and public health emergency response, and provide a scientific path for the sustainable development of the TCM industry.