Heterogeneous graph construction and node representation learning method of Treatise on Febrile Diseases based on graph convolutional network

Heterogeneous graph construction and node representation learning method of Treatise on Febrile Diseases based on graph convolutional network

Objective: To construct symptom-formula-herb heterogeneous graphs structured Treatise on Febrile Diseases (Shang Han Lun,《伤寒论》) dataset and explore an optimal learning method represented with node attributes based on graph convolutional network (GCN). Methods: Clauses that contain symptoms, formulas...

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Bibliographic Details
Main Authors:	Junfeng YAN, Zhihua WEN, Beiji ZOU
Format:	Article
Language:	English
Published:	KeAi Communications Co., Ltd. 2022-12-01
Series:	Digital Chinese Medicine
Subjects:	Graph convolutional network (GCN) Heterogeneous graph Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》) node representations on heterogeneous graph node representation learning
Online Access:	http://www.sciencedirect.com/science/article/pii/S2589377722000775

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