Knowledge Discovery of Selection Rules for Acupuncture Points in Respiratory Diseases Therapy Based on Partial-Ordered Structure Diagrams

This paper presents a knowledge discovery method of selection rules for acupuncture points in respiratory diseases therapy based on the theory of Structural Partial-Ordered Attribute Diagram and association rule mining. First, we briefly introduced the basic definitions of Structural Partial-Ordered Attribute Diagram and association rule mining theory. Then, we transformed the data of a Traditional Chinese Medicine treatise into formal context and transaction database. Finally, we explained knowledge discovery process by analyzing the formal context of respiratory diseases. It was concluded that the method proposed in this paper works well in discovering new knowledge from medical treatises and clinical cases of acupuncture treatment. The method provided a scientific and advanced technological means for the heritage of Traditional Chinese Medicine.