Research On Expert Knowledge Fusion In Virtual Health Community

The virtual health community is a window to serve the public under the mode of"Internet + Medical".By taking inventory and integrating existing online and offline resources,and constructing the medical knowledge interaction and sharing platform between patients and doctors,it gradually becomes an important channel for medical institutions to provide convenient,high-quality and efficient information services to the public.The virtual healthy community contains a lot of valuable information and knowledge,which provides new research fields for medical and health knowledge organization and knowledge fusion,and how to organize and excavate the expert information and knowledge of the virtual health community of fragmentation,heterogeneity and text becomes the hotspot of research.Knowledge fusion plays a crucial role as the intermediate part of knowledge base construction.It is a key step for the expert knowledge organization and presentation of virtual health community.The expert knowledge management problem in the field of medical health is mainly to solve the problem of knowledge base construction of expert knowledge conceptual entities such as symptoms,diagnosis,complications,treatment and prevention.Therefore,expert knowledge representation and knowledge base construction can be carried out by processing and integrating the data sources of existing medical ontology and various virtual health communities(including disease encyclopedia,medical science articles,doctor-patient Q&A,etc.)using knowledge extraction and knowledge fusion.The main contributions of this paper are summarized as follows:(1)By using the theory and methods and techniques of knowledge integration,I have developed a system framework based on the knowledge of the virtual health community,and designed the process of data collection and processing,expert knowledge extraction,expert knowledge fusion,and detailed the specific work and methods of each stage,so as to realize effective extraction and integration of health medical expert knowledge in the network environment,and provide network knowledge source and reference for medical health knowledge service and decision-making.(2)This paper builds a knowledge base of "hypertension" disease ontology based on the community disease encyclopedia,popular science articles and related standard documents.Through the knowledge extraction and knowledge fusion of the text data of the doctor-patient Q&A platform,the validity of knowledge is expanded.At the same time,based on the D-S evidence fusion algorithm,the basic probability distribution of the evidence is solved based on the rules and statistical methods,and the knowledge recommendation of "hypertension complications-antihypertensive drugs" is realized,and this part of knowledge is integrated into the ontology knowledge base to enhance the reasoning ability of hypertensive ontology.