|本期目录/Table of Contents|

[1]王晶晶,罗兰君,安天成,等.知识图谱在应急管理领域应用研究综述*[J].中国安全生产科学技术,2025,21(4):189-194.[doi:10.11731/j.issn.1673-193x.2025.04.025]
　WANG Jingjing,LUO Lanjun,AN Tiancheng,et al.Review on application of knowledge graph in field of emergency management[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2025,21(4):189-194.[doi:10.11731/j.issn.1673-193x.2025.04.025]
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知识图谱在应急管理领域应用研究综述*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
21
期数:
2025年4期
页码:
189-194
栏目:
职业安全卫生管理与技术
出版日期:
2025-04-30

文章信息/Info

Title:
Review on application of knowledge graph in field of emergency management
文章编号:
1673-193X(2025)-04-0189-06
作者:
王晶晶; 罗兰君; 安天成; 文雨; 翟羽佳
（1.北京市科学技术研究院，北京 100035；
2.天津师范大学 管理学院，天津 300387；
3.武汉大学 信息管理学院，湖北 武汉 430072）
Author(s):
WANG Jingjing;  LUO Lanjun;  AN Tiancheng;  WEN Yu;  ZHAI Yujia
(1.Beijing Academy of Science and Technology,Beijing 100035,China;
2.School of Management,Tianjin Normal University,Tianjin 300387,China;
3.School of Information Management,Wuhan University,Wuhan Hubei 430072,China)
关键词:
知识图谱; 应急管理; 风险管理; 系统性文献综述; 智能决策支持
Keywords:
knowledge graph;  emergency management;  risk management;  systematic literature review;  intelligent decision support
分类号:
X913.4
DOI:
10.11731/j.issn.1673-193x.2025.04.025
文献标志码:
A
摘要:
为应对复杂多变的突发事件并克服传统应急管理在信息融合与实时决策中的不足，通过系统性文献综述，梳理知识图谱在应急管理各阶段的研究现状与典型应用，从预防与应急准备、监测与预警、应急处置与救援、事后恢复与重建4方面探讨知识图谱在知识库构建、潜在风险识别、优化资源调度与修复流程优化等方面的应用，并指出其未来发展应用。研究结果表明：知识图谱可在多源数据融合与语义推理上显著提升应急管理的精度与响应速度，同时与人工智能技术的结合进一步赋能应急管理体系的发展。研究结果可为后续相关理论与实践提供可借鉴的方向与思路。
Abstract:
To address the challenges of complex emergencies and overcome the limitations of traditional emergency management in information integration and real-time decision-making,a systematic literature review was conducted to summarize the research status and typical application of knowledge graph in various phases of emergency management.The application of knowledge graph was explored from four aspects: prevention and emergency preparedness,monitoring and early warning,emergency response and rescue,and post-event recovery and reconstruction,focusing on knowledge base construction,potential risk identification,resource scheduling optimization,and restoration process improvement.The future development directions were also identified.The results show that the precision and response speed of emergency management are significantly enhanced by the knowledge graph in multi-source data fusion and semantic reasoning.Furthermore,the integration with artificial intelligence technologies further empowers the development of emergency management system.The research results can provide reference directions and ideas for subsequent theories and practice in related fields.

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备注/Memo

备注/Memo:
收稿日期： 2024-12-24
* 基金项目： 北京市科技新星计划项目(Z211100002121162)；北京市科技新星交叉合作课题项目（20230484417）
作者简介： 王晶晶，博士，副研究员，主要研究方向为城市应急管理。
通信作者： 翟羽佳，博士，副教授，主要研究方向为应急信息学等。
更新日期/Last Update: 2025-04-28