基于Neo4j的城市地下管道信息知识图谱构建研究  

Study on construction of knowledge graph for urban underground pipeline information based on Neo4j

作　　者：史政一 吕君可 黄弘[1] SHI Zhengyi;LYU Junke;HUANG Hong(School of Safety Science,Tsinghua University,Beijing 100084,China)

机构地区：[1]清华大学安全科学学院,北京100084

出　　处：《中国安全生产科学技术》2024年第6期5-10,共6页Journal of Safety Science and Technology

基　　金：国家重点研发计划项目(2022YFF0606900)。

摘　　要：为更好地支撑城市地下管道的探测作业,更系统、灵活地管理地下管道知识数据库,以相关国内标准、规范为研究基础,通过实体提取、知识整合等过程,建立城市地下管道信息知识图谱。将知识图谱存储在图数据库Neo4j中,提出基于数据-知识融合的辅助探测决策应用框架,进而提供实时、精准的知识查询接口。研究结果表明:构建的知识图谱可以辅助地下管道开挖工程的探测决策过程,一定程度上为推进地下管道数据-知识融合探测体系建成提供参考。In order to better support the detection operation of urban underground pipelines and manage the underground pipeline knowledge database more systematically and flexibly,based on relevant domestic standards and specifications,the knowledge graph of urban underground pipeline information was established through entity extraction and knowledge integration.The knowledge graph was stored in the graph database Neo4j,and an auxiliary decision-making framework of detection based on data-knowledge fusion was proposed to provide the real-time and accurate knowledge query interface.The research results show that the constructed knowledge graph can assist the detection decision-making process of underground pipeline excavation engineering,and promote the construction of underground pipeline data-knowledge fusion detection system.

关 键 词：城市地下管道 知识图谱 实体提取 知识存储 

分 类 号：X913[环境科学与工程—安全科学] X937