Entity Alignment Based on Knowledge Graph of Chinese Electronic Medical Record
Entity alignment is essential to fuse the medical knowledge graphs since the phenomenon of knowledge overlap and complementarity is common in different medical knowledge graphs.However,according to our research,there is not yet a complete solution for entity alignment in the medical field.Therefore,we propose a standardized entity alignment process based on the Chinese electronic medical record knowledge graph,which pro-vides a feasible scheme for entity alignment in the medical field.Meanwhile,according to the characteristic of the structural heterogeneity of the medical knowledge graph,we design a Dual-view Parallel Graph Neural Network(DuPNet)to solve the problem of entity alignment in the medical field,which achieves good results.
medical knowledge graphChinese electronic medical recordentity alignmentstructual heterogeneityparallel graph neural network
万方数据
维普
