Article(id=1282037426931609629, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282037390130790473, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.12.0044, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1750348800000, receivedDateStr=2025-06-20, revisedDate=1760025600000, revisedDateStr=2025-10-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1783591141684, onlineDateStr=2026-07-09, pubDate=1766851200000, pubDateStr=2025-12-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783591141684, onlineIssueDateStr=2026-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783591141684, creator=13701087609, updateTime=1783591141684, updator=13701087609, issue=Issue{id=1282037390130790473, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='12', pageStart='1', pageEnd='259', issueExtLink='null', onlineDate='null', pubDate='1766851200000', pubDateStr='2025-12-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783591132910, creator='13701087609', updateTime=1783593783109, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282048505929777979, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282037390130790473, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282048505929777980, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282037390130790473, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1, endPage=7, ext={EN=ArticleExt(id=1282037427216822302, articleId=1282037426931609629, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=A review of technology development of large language model and knowledge graph in field of construction safety, columnId=1149733271128420907, journalTitle=China Safety Science Journal, columnName=Safety social science and safety management, runingTitle=null, highlight=null, articleAbstract=

In order to clarify the potential research value and application prospects of LLMs and KG technologies in the field of construction safety, the existing problems in the knowledge-driven digital transformation of this domain were comprehensively analyzed, and the current state of technological development regarding knowledge graphs and large language models within it was reviewed. First, relevant literature was retrieved from the China National Knowledge Infrastructure (CNKI) and Web of Science(WoS) databases to define the scope of analysis. Then, the existing problems and challenges in the digital transformation of construction safety were analyzed, and the necessity of introducing KG and LLM was elaborated. Subsequently, the technological development of KG and LLM, along with the current status of their application research in construction safety, was briefly described. Preliminary achievements in the integrated application of KG and LLM within the construction safety domain were explored. Finally, the shortcomings of existing research were summarized, and future research directions are outlined. The results indicate that LLMs and KG technologies have demonstrated significant application potential in various scenarios within construction safety, including knowledge management, risk identification, and intelligent decision-making, highlighting considerable prospects for future implementation. However, current research still faces challenges such as a lack of real-time capabilities and insufficient integration. Future efforts should focus on establishing comprehensive and precise construction safety KG and exploring novel approaches for the integrated application of LLM and KG.

, authors=Rongyong ZHAO¹, Xingzhu PENG¹, Bingyu WEI¹, Guoyi ZENG², Fengnian LIU³, Peng YAN⁴, authorsList=Rongyong ZHAO, Xingzhu PENG, Bingyu WEI, Guoyi ZENG, Fengnian LIU, Peng YAN, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1282037428001157153, articleId=1282037426931609629, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=大语言模型与知识图谱在建筑安全领域的技术发展综述, columnId=1149733271296193071, journalTitle=中国安全科学学报, columnName=安全社会科学与安全管理, runingTitle=null, highlight=null, articleAbstract=

为厘清建筑安全领域中大语言模型（LLM）与知识图谱（KG）技术的潜在研究价值和应用前景，综合分析建筑安全领域知识驱动的数字化转型现存问题，梳理LLM和KG在该领域的技术发展现状。首先，在中国知网（CNKI）和科学网（WoS）中检索相关文献，确定分析范围；其次，分析建筑安全生产数字化转型的现存问题与挑战，并阐述LLM和KG引入的必要性；然后，简述LLM和KG技术发展及其在建筑安全领域的应用研究现状，探讨LLM和KG在建筑安全领域的融合应用初步成果；最后，总结现有研究不足之处，展望未来发展。结果表明：LLM与KG技术在建筑安全知识管理、风险识别、智能决策等多个场景中已展现出显著的应用潜力，表现出可观的应用前景，但当前研究仍存在实时性缺乏、融合不足等问题。未来应着手建立全面精准的建筑安全KG，深入探究LLM与KG融合应用新思路。

, authors=赵荣泳副教授¹, 彭星竹¹, 韦炳宇¹, 曾国毅², 刘丰年³, 闫鹏⁴, authorsList=赵荣泳副教授, 彭星竹, 韦炳宇, 曾国毅, 刘丰年, 闫鹏, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=owalGXWIhJ7b6T1F+6fPuA==, magXml=o6S8+VG2HOE7yHLxCvcc9Q==, pdfUrl=null, pdf=H3A16lCcsDH+y+QOkYNmMg==, pdfFileSize=4009756, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=bCJpdlKlUzor42VWh/Ck2A==, mapNumber=null, fund=null)}, authors=[Author(id=1282037430635180079, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282037426931609629, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=zhaorongyong@tongji.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1282037430744231985, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282037426931609629, authorId=1282037430635180079, language=EN, stringName=Rongyong ZHAO, firstName=Rongyong, middleName=null, lastName=ZHAO, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1282037430836506674, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282037426931609629, authorId=1282037430635180079, language=CN, stringName=赵荣泳副教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹同济大学 电子与信息工程学院CIMS研究中心，上海 201804, bio={"content":"

赵荣泳（1976—），男，山东济南人，博士，副教授，主要从事公共安全系统工程和复杂系统优化等方面的研究。E-mail: zhaorongyong@tongji.edu.cn。

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赵荣泳（1976—），男，山东济南人，博士，副教授，主要从事公共安全系统工程和复杂系统优化等方面的研究。E-mail: zhaorongyong@tongji.edu.cn。

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