Application Research of Knowledge Mapping in TCM Health

  • Weixue Hao


Objective: In the field of Web search and general field, a large number of large-scale knowledge map libraries have been formed, but the
construction of knowledge maps in the fields of medicine and traditional Chinese medicine is still in its infancy, although there are large-scale
medical ontology libraries. However, there are still few studies on the construction of specialized medicine, especially the TCM knowledge
map library, which greatly hinders the information application and sharing of TCM concept knowledge.
Methods: For the map construction of the main conceptual entities such as symptoms, syndromes, diseases and traditional Chinese medicine
in the field of traditional Chinese medicine, the corresponding schema pattern (Schema) was designed to determine the basic categories,
category attributes and semantic relations of the map. The Protege Ontology Editor adds constraints to the entities in the TCM knowledge
map and their relationships, and uses Protege to graphically display some of the knowledge in the knowledge map. Finally, based on the
formed knowledge map, the open-source toolkit Jena and the inference rules based on the logic of TCM diagnosis and treatment are used to
carry out the model analysis and application of knowledge reasoning based on knowledge map.
Conclusion: Knowledge graph is carried out in the era of big data. The important data resources of knowledge management and application
have become the key technical basis for search engine semantic retrieval and knowledge-based reasoning and decision-making in various
fields. By integrating various data sources, this paper studies the construction of TCM health knowledge maps with symptoms, syndromes,
diseases and medicines as the main entities. The analysis results show that it has certain feasibility and application value.

How to Cite
Hao, W. (2018, October 17). Application Research of Knowledge Mapping in TCM Health. Journal of Clinical and Experimental Medicine, 2(3), 7.
Clinical and Experimental Medicine