Title: Knowledge discovery for spleen yang deficiency syndrome based on attribute partial order structure diagram

Authors: Hui Meng; Xiaoying Han

Addresses: College of Electrical Engineering, Yanshan University, Qinhuangdao 066004, Hebei, China ' College of Electrical Engineering, Yanshan University, Qinhuangdao 066004, Hebei, China

Abstract: Syndromes and medications in Traditional Chinese Medicine (TCM) have been studied by advanced information technology in the modernisation of TCM, promoting the development of knowledge discovery in TCM. In this paper, based on the method of Attribute Partial Order Structure Diagram (APOSD), syndrome-symptom APOSD and prescription-herb APOSD are constructed for spleen yang deficiency syndrome, which is a common syndrome in TCM. The common symptoms and specific symptoms of spleen yang deficiency syndrome are extracted from the syndrome-symptom APOSD. The association rules among herbs in the prescriptions for treating spleen yang deficiency syndrome are visualised on the prescription-herb APOSD, and herb pairs and herb groups are extracted. Compared with Apriori algorithm, APOSD not only obtains important association rules, but also shows the compositions of prescriptions in the diagram. APOSD provides a new scientific research method for TCM.

Keywords: attribute partial order structure diagram; knowledge discovery; spleen yang deficiency syndrome; symptom patterns; prescription compatibility.

DOI: 10.1504/IJCAT.2020.111086

International Journal of Computer Applications in Technology, 2020 Vol.64 No.1, pp.92 - 99

Received: 03 Dec 2019
Accepted: 25 May 2020

Published online: 21 Oct 2020 *

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