Tacit knowledge is the core of knowledge

and traditional Chinese medicine (TCM) tacit knowledge is an important part of TCM science. Externalization of tacit knowledge in TCM is a necessary condition for effective exchange and sharing of TCM knowledge

and important guarantee to promote the development and innovation of TCM. However

the process of externalizing tacit knowledge is affected by many factors. Data mining technology can extract unknown

potential

useful information and knowledge hidden in a large number of incomplete

fuzzy

random practical application data. By taking advantages of data mining technology in extracting implicit knowledge

this study focused on externalization of tacit knowledge in TCM with support of association rules analysis

complex system entropy clustering analysis

decision tree analysis

factor analysis

bayesian network analysis and other data mining technologies. Through literature analysis and collation

with specific data mining technology as classification criteria and main line

the study involved individual physicians

ancient medical classics and modern clinical researches

with content involving TCM pathogenesis

the rule of treatment

dialectical law

regularity of using prescriptions

regularity of herbal pairs and composition and other aspects of tacit TCM knowledge. The results showed that

according to the characteristics of the research content

specific data mining technology can be selected to externalize tacit TCM knowledge

which is beneficial to expand the channels of externalizing tacit knowledge of TCM

and improve the externalization of tacit TCM knowledge and maximize externalization and sharing of tacit knowledge in TCM. Based on the active role of data mining technology in the externalization of tacit knowledge of TCM

the data mining and inheritance platforms with TCM characteristics shall be popularized

integrated and optimized to promote the inheritance and innovation of TCM.