Research hotspot and evolution trend analysis of TCM talent training based on clustering algorithm

This paper uses TF-IDF and Kleinberg algorithms to map the literature in the field of TCM talent training included in the core journals of CNKI from 2014 to 2024 from the number of publications, publishing organization, keyword clustering and mutation, analyze the research hot spots and evolution trends in the field of TCM talents in China, and draw research conclusions and put forward suggestions. The number of published articles is increasing year by year, which can strengthen the exchange, cooperation and resource sharing among research institutions, and emerge high hot topics such as traditional Chinese medicine culture, innovative talents, teacher education, innovation and entrepreneurship education. It is suggested to break the traditional shackles, innovate the training mode of TCM talents, and improve the quality and level of training. In-depth study of the talent training system, teaching methods, evaluation system and other key issues, and constantly innovate the education mode and training mechanism.