交通信息与安全2025，Vol.43Issue(3)：10-23,14.DOI:10.3963/j.jssn.1674-4861.2025.03.002
基于多源异构信息的船舶碰撞事故防控知识图谱研究
A Knowledge Graph of Ship Collision Prevention and Control Based on Multi-source Heterogeneous Information
摘要
Abstract
Traditional research on water transportation accidents mainly focuses on exploring the causative factors and corresponding complex relationship with various accidents,which is insufficient in reflecting the evolution of traffic accidents and the complicated interactions between elements including people,vessels,cargo,environment,administration,and information in the maritime system.To fill the gap,this paper proposes a methodology for devel-oping a water transportation knowledge graph based on multi-source heterogeneous information and applies it to the accident prevention and control strategies development.A framework for ship collision knowledge is designed,con-sidering the components of accidents,e.g.,event,spatiotemporal ship behavior,maritime accidents causative fac-tors,accidents consequences,corresponding responsibility roles,and disposal decision-making.A knowledge extrac-tion model is employed to extract the maritime safety knowledge,which is based on Chinese Bidirectional Encoder Representations from Transformers Whole Word Masking and is named as Chinese-bert-wwm model.Thirdly,the SCPCKG(ship collision prevention and control knowledge graph)is developed based on the Neo4j database,which contains 35 784 entities from 15 entity types and 325 097 relationships from 39 relationship types.The scale of the SCPCKG is significantly larger than that of existing knowledge graphs in the field of water transportation,and the accuracy of automated knowledge extraction based on the proposed SCPCKG reaches 85%,which is higher than the existing models,such as Hidden Markov Models(HMMs)and Conditional Random Fields(CRFs).Specifically,the F1-score value for identifying"ship","person characteristics","time","person",and"laws"entities reaches 95%,91%,98%,88%,and 88%,respectively;the F1-score value of relationship extraction reaches 94%.The re-sults show that the proposed Chinese-bert-wwm model can enhance the generalized capability of the knowledge ex-traction model by extracting the semantic features of ship collision accidents from the accident reports,and the pro-posed SCPCKG can be used for the knowledge representation of ship collision accidents and inversion of accidents for maritime administrators,improving the effectiveness of the water transportation management.关键词
水上交通安全/船舶碰撞事故/知识图谱/Chinese-bert-wwmKey words
waterborne transportation safety/ship collision accidents/knowledge graphs/Chinese-bert-wwm分类
交通工程引用本文复制引用
余红楚,郭正,魏天明,许磊,方庆龙..基于多源异构信息的船舶碰撞事故防控知识图谱研究[J].交通信息与安全,2025,43(3):10-23,14.基金项目
国家重点研发计划项目(2022YFC3302703)、国家自然科学基金项目(42101429、42371415)、中国科学技术协会青年人才托举工程项目(YESS20220491)、海南省教育厅项目(Hnjg2024-284)资助. （2022YFC3302703）
