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In recent years, the application of knowledge discovery method to the field of the traditional Chinese medicine (TCM) gains more attention to researchers. It is necessary to have a visual mining for hidden knowledge in the massive and complicated data of prescription, which embody important knowledge of treatment for different syndrome. The spleen deficiency syndrome is one of the common syndromes of TCM, but there have many problems needed to be discovered and perfected further. In this paper, we present a visual analysis method named attribute partial ordered structure diagram (APOSD) for mining knowledge of prescription compatibility law for spleen deficiency syndrome. A formal context is formed based on prescriptions and drugs recorded in literature. Then it is optimized and computed to construct APOSD for visualization. The useful knowledge can be mined from the APOSD. The result shows that APOSD can discover new knowledge of prescription compatibility.

Knowledge Discovery of Prescription for Spleen Deficiency Syndrome Base on Attribute Partial Ordered Structure Diagram