水力发电学报2026，Vol.45Issue(8)：108-124,17.DOI:10.11660/slfdxb.20260810
大坝安全知识图谱的深度语义理解与结构化建模路径研究
Study on deep semantic understanding and structured modeling path of dam safety knowledge graphs
摘要
Abstract
Aimed at the issue of knowledge islands between water conservancy project data texts,this paper presents a dam safety knowledge graph construction method based on the UIE framework and the SE-RE-Joint model.We use a seven-step method to construct a multi-layer domain ontology library of main structure,affiliated buildings,and comprehensive evaluation.After data preprocessing,fine-tuning of small samples is used to realize preliminary entity recognition.We complete entity recognition and relationship extraction through semantic enhanced coding,relying on the bidirectional GRU to capture sequence dependence and CRF to optimize label sequence consistency.And,a Neo4j graph database is used to store knowledge.Test results show that the UIE+SE-RE-Joint model extracts 25,000 entities and 31,000 relational pairs,and achieves a prediction accuracy higher than 84%.The four types of errors-entity conflicts,boundary ambiguities,type confusions,and relationship misjudgments-all are lowered significantly relative to the comparison model.The map supports knowledge visualization and data retrieval;Through Python-based implementation,it completes knowledge dynamic updating,knowledge reasoning,and risk positioning,assisting the intelligent diagnosis in dam safety management.关键词
大坝安全/知识图谱/工程资料文本/语义增强/深度学习模型/知识抽取Key words
dam safety/knowledge graph/engineering data text/semantic enhancement/deep learning model/knowledge extraction分类
建筑与水利引用本文复制引用
龚琳玲,陈波,严克伍,吕国旭..大坝安全知识图谱的深度语义理解与结构化建模路径研究[J].水力发电学报,2026,45(8):108-124,17.基金项目
国家自然科学基金面上项目(52079049) （52079049）
第七批国家特支计划青年拔尖项目(B22053) （B22053）
