摘要
目前,新冠肺炎传播迅速,影响广泛,对全球的人类生存和经济都造成了重大影响。已有的流行病学分析方法侧重于统计分析,忽视了病例间的时空传播关系和语义关联关系。通过构建新冠肺炎病例知识图谱进行可视化并加以分析,可以结合语义和时空特征挖掘新冠肺炎传播过程和发展趋势。以郑州市疾病预防控制中心发布的病例通报数据为基础,针对人群活动模型组成要素,构建了新冠肺炎病例知识图谱本体层和数据层。在构建知识图谱后,综合应用甘特图、平行坐标图、关联关系图等可视化方法,设计了一个基于新冠肺炎病例知识图谱的交互式可视分析原型系统,发现新冠肺炎病例的多维度特征、病例活动和传播过程。
Covid-19 has spread rapidly and affected a wide range of people,with significant impacts of human health and socio-economic.The epidemiological analysis focus on statistical analysis,however it ignore the temporal relationship and semantic relationship between cases.This paper proposes a visual analysis method based on Covid-19 patients knowledge graph,to explore the spread and development trend of Covid-19.Firstly,we provide the ontology-layer and data-layer of the knowledge graph based on the features of crowd activity.Then,we design and implement a visual analysis system which also provides a set of interactions to involve users in the entire process of the epidemiological data analysis.To validate our approach,we utilize the data sets from Zhengzhou and show how our method can find multi-dimensional features,crowd activity and transmission process.
作者
李佳
刘海砚
刘俊楠
刘建湘
LI Jia;LIU Haiyan;LIU Junnan;LIU Jianxiang(Information Engineering University,Zhengzhou 450001)
出处
《信息工程大学学报》
2021年第5期606-612,共7页
Journal of Information Engineering University
基金
国家自然科学基金资助项目(41801313,41901397)。
关键词
新冠肺炎
知识图谱
可视分析
时空关系
语义关系
Covid-19
knowledge graph
visual analysis
spatiotemporal relationship
semantic relationship
