COVID-19地理知识图谱构建分析——以江苏省为例  

Geographical Knowledge Graph Construction Analysis of COVID-19:Taking Jiangsu Province as an Example

作　　者：张雷雨[1] 刘杰 ZHANG Leiyu;LIU Jie(School of Architectural Engineering,Lianyungang Technical College,Lianyungang 222006,China;School of Marine Technology and Geomatics,Jiangsu Ocean University,Lianyungang 222005,China)

机构地区：[1]连云港职业技术学院建筑工程学院,江苏连云港222006 [2]江苏海洋大学海洋技术与测绘学院,江苏连云港222005

出　　处：《连云港职业技术学院学报》2022年第1期6-11,共6页Journal of Lianyungang Technical College

基　　金：江苏省高等学校自然科学研究项目资助(21KJD420001);江苏省高校“青蓝工程”资助项目(2020)。

摘　　要：新型冠状病毒肺炎已经形成全球化的蔓延趋势,迫切需要从时空维度认知疫情的传播机理。传统的知识图谱方法无法探测疫情地理知识和回溯疫情发展时空过程,鉴于此,研究并实现了面向新冠肺炎的地理知识图谱构建与可视化分析。首先,借助数据动态获取手段得到确诊患者详细信息与时空活动轨迹数据,进行关系抽取和本体库构建,形成新冠肺炎地理知识图谱;其次,基于新冠肺炎地理知识图谱系统,分别进行了疫情时空分析、重点城市疫情传播时空溯源。结果表明:利用地理知识图谱方法对海量病患信息整合与时空关系抽取,能够揭示疫情的传播过程,为突发传染病事件的科学防控和深入研究提供参考。COVID-19 has formed the spreading trend of globalization,and it is urgent to understand the transmission mechanism of the epidemic from the spatial and temporal dimension. In view of the inability of traditional knowledge mapping methods to detect epidemic geographic knowledge and backdate the spatial and temporal process of epidemic development,thus the geographic Knowledge Graph construction and visual analysis of COVID-19 were studied and realized. Firstly, detailed information of confirmed patients and spatiotemporal activity trajectory data were obtained by dynamic data acquisition, relationship extraction and ontology database construction were conducted to form a COVID-19 geographic Knowledge Graph. Secondly,based on the Graph system,the spatiotemporal analysis and back trace of epidemic transmission in major cities were conducted respectively. The findings show that the integration of massive patient information and spatial and temporal relationship extraction can reveal the transmission process of the epidemic, and provide reference for scientific prevention and control and indepth research.

关 键 词：新型冠状病毒肺炎 地理时空 知识图谱 

分 类 号：R181.3[医药卫生—流行病学]