摘要
目前,随着全球新型冠状病毒肺炎(coronavirus disease 2019,COVID-19)病例数量不断增加,疫情时空传播过程变得越来越复杂。传统的传播过程研究主要是在宏观上研究传染病的整体传播规律或趋势,不能在个体层面分析具体病例之间的传播关系,无法精准定位疫情传播路径,很难支持传染病的精准防控,亟需兼顾时空和语义特征研究传染病传播过程。首先在解析COVID-19病例数据基础上,利用知识图谱技术提出了构建适应多样化描述方式的COVID-19病例活动知识图谱;然后从传播事件角度设计了COVID-19病例活动知识图谱本体规则,完成了模式层的构建;并以流行病调查数据为基础,对病例数据进行解析、事件实体识别和数据存储,完成了数据层的构建;最后,通过图数据库和B/S端构建原型系统进行实验验证。结果表明,通过COVID-19病例活动知识图谱对传播过程推理、关键节点分析和活动轨迹回溯等层面进行验证,方法较为有效,且具有一定可行性。
At present,the number of coronavirus disease 2019(COVID-19)cases worldwide is increasing,the spatio temporal spread of the epidemic becomes more and more complicated.The traditional researches on the transmission process is mainly focus on transmission trends of infectious diseases at the macro level.It is impossible to analyze the transmission relationship between specific cases at the individual level,to accurately locate the transmission paths of the epidemic,and it is difficult to support the precise prevention of infectious diseases.So,it is an urgent need to study the transmission process of infectious diseases on both of the semantic and spatio-temporal features.Based on the analysis of COVID-19 epidemic cases data,we construct the COVID-19 cases activity knowledge graph,which adapts to various description methods.Then,we design the ontology rules to complete the construction of the pattern layer.The epidemiological survey data has been analyzed to recognize the event entities,and to complete the construction of data layer.Finally,through the graph database and the B/S pattern to build a prototype system for experimental verification.The results show that it is effective and feasible to analyze the transmission process,infection relationship,key nodes and activity trajectory through the COVID-19 cases activity knowledge graph.
作者
陈晓慧
刘俊楠
徐立
李佳
张伟
刘海砚
CHEN Xiaohui;LIU Junnan;XU Li;LI Jia;ZHANG Wei;LIU Haiyan(Institute of Data and Target Engineering,Information Engineering University,Zhengzhou 450001,China;Institute of Geospatial Information,Information Engineering University,Zhengzhou 450001,China)
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2020年第6期816-825,共10页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金(41801313,41901397)。
关键词
新型冠状病毒肺炎
传染病调查
活动知识图谱
知识图谱可视化
coronavirus disease 2019(COVID-19)
epidemiological survey
activity knowledge graph
visualization of knowledge graph
