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面向重大突发事件应急管理的事件知识图谱构建及场景应用

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探究重大突发事件的知识建模及应用场景,以事件为中心关联应急管理知识,有助于相关部门全面感知突发事件发生、发展态势,提升应急管理能力.本研究基于事件演变与属性关联的知识驱动视角,提出一种事件知识图谱的构建流程和方法体系,同时,给出相适用的应急管理服务场景.首先,通过事件知识建模设计事件知识图谱的模式层,将突发事件、承灾事件及应急管理事件知识相关联;其次,通过事件知识抽取、事件知识融合及事件知识存储等步骤,构建事件知识图谱数据层;最后,以暴雨类自然灾害突发事件为例进行验证,表明事件知识图谱不仅能够描述突发事件的类型、强度及其时空演变趋势,还能反映其如何作用于承灾载体以及在应急管理中发挥的实际效用,为突发事件的科学应对提供支撑.
Construction and Application of Event Knowledge Graph for Major Emergency Response Management
To explore knowledge modeling and applications in emergencies and associate emergency management knowl-edge with events,this study aims to help relevant departments scientifically understand the occurrence and evolution of emergencies and improve emergency management capabilities.Based on a knowledge-driven perspective of event evolu-tion and property association,this study proposes a process and methodology for constructing an event-knowledge graph.First,the schema layer of the event-knowledge graph is designed through event knowledge modeling,associating knowl-edge of emergencies,disaster-bearing events,and response management events.Second,the data layer of the event-knowl-edge graph is constructed through steps including event knowledge extraction,fusion,and memory.Finally,the study de-velops an example of an event-knowledge graph for heavy rainfall-related natural disasters and proposes applicable emer-gency management service scenarios.An example validation of a natural storm disaster emergency was conducted.The re-sults demonstrate that the event-knowledge graph not only describes the type and intensity of emergencies and their spatio-temporal evolution trends but also illustrates their impact on disaster-bearing carriers and their practical utility in emergen-cy management.This provides support for a scientific response to emergencies.

major emergencyevent knowledge graphresponse managementknowledge modelingknowledge extraction

周红磊、张海涛、刘伟利、刘彦辉

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吉林大学商学与管理学院,长春 130012

吉林大学信息资源研究中心,长春 130012

吉林大学国家发展与安全研究院,长春 130012

重大突发事件 事件知识图谱 应急管理 知识建模 知识抽取

2024

情报学报
中国科学技术情报学会 中国科学技术信息研究所

情报学报

CSTPCDCSSCICHSSCD北大核心
影响因子:1.296
ISSN:1000-0135
年,卷(期):2024.43(12)