Article(id=1281683242591949133, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281683189131359212, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.05.0883, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736611200000, receivedDateStr=2025-01-12, revisedDate=1742486400000, revisedDateStr=2025-03-21, acceptedDate=null, acceptedDateStr=null, onlineDate=1783506697556, onlineDateStr=2026-07-08, pubDate=1748361600000, pubDateStr=2025-05-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783506697556, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783506697556, creator=13701087609, updateTime=1783506697556, updator=13701087609, issue=Issue{id=1281683189131359212, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='5', pageStart='1', pageEnd='268', issueExtLink='null', onlineDate='null', pubDate='1748361600000', pubDateStr='2025-05-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783506684811, creator='13701087609', updateTime=1783589333681, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282029843684504545, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281683189131359212, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282029843684504546, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281683189131359212, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=56, endPage=63, ext={EN=ArticleExt(id=1281683242810052942, articleId=1281683242591949133, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Data-driven correlation analysis and early warning strategy for potential safety hazards in construction, columnId=1149733269173878863, journalTitle=China Safety Science Journal, columnName=Safety engineering technology, runingTitle=null, highlight=null, articleAbstract=

To explore the potential early warning value of construction safety hazard data and improve the efficiency of hazard identification and control, this study investigated a data-driven approach for the association analysis and early warning strategy of construction safety hazards by integrating text mining, association rule mining, and complex network theory. First, 1 405 construction safety inspection records in 2023 were standardized and dimensionally reduced using text mining techniques, resulting in the extraction of 67 safety hazard features. Then, 70 frequent itemsets and 125 strong association rules were obtained using the Apriori algorithm, and the types of hazard associations were identified. Subsequently, a hazard feature network was constructed based on complex network theory. Key hazard features were identified through structural and node-level indicators, combined with feature modularity analysis. Finally, a feature-driven early warning strategy was proposed. The results show that text mining effectively reduces the dimensionality of unstructured hazard data. The hazard feature network based on association rules successfully reveals hidden associations within the data and enhances the reliability of early warning information, providing clear direction and reference for on-site hazard detection. The early warning strategy helps address the issues of disorder and inefficiency in traditional hazard inspections.

, authors=Dalin ZENG, Fangzheng XIAO^**, Zhichao JIANG, Haiyang ZHANG, authorsList=Dalin ZENG, Fangzheng XIAO, Zhichao JIANG, Haiyang ZHANG, authorCompany=null, correspAuthors=Fangzheng XIAO, 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=1281683244844290385, articleId=1281683242591949133, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=数据驱动下建筑施工安全隐患关联分析与预警策略, columnId=1149733269727526997, journalTitle=中国安全科学学报, columnName=安全工程技术, runingTitle=null, highlight=null, articleAbstract=

为深入挖掘施工安全隐患数据的潜在预警价值，提高隐患排查治理效率，利用文本挖掘技术、关联规则和复杂网络理论，研究数据驱动下建筑施工安全隐患关联分析与预警策略。首先，借助文本挖掘技术标准化降维处理某地2023年度的1 405条建筑施工安全巡检记录，并提取出67个安全隐患特征；其次，通过Apriori关联规则算法得到70个频繁项集，125条强关联规则，并确定隐患的关联类型；然后，结合复杂网络理论构建施工安全隐患特征网络，基于网络结构指标和个体指标分析，并结合特征模块化分析，辨识关键安全隐患特征；最后，提出一种基于特征数据驱动的安全隐患预警策略。结果表明：文本挖掘技术能有效降维非标准化隐患数据；基于关联规则的隐患特征网络能充分挖掘隐患数据间的潜在关联，加强隐患预警信息的可靠性；预警策略有助于解决传统隐患排查中无序、低效的问题。

, authors=曾大林教授, 肖方正^**, 姜志超, 张海洋, authorsList=曾大林教授, 肖方正, 姜志超, 张海洋, authorCompany=null, correspAuthors=肖方正, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=RKdshk4g6NPcE7tljAYapw==, magXml=XiT1WxZYXjMKAwlWR6ZcIw==, pdfUrl=null, pdf=uafxrgbClOaDpVpxrE11xA==, pdfFileSize=3067526, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=AjjEl6qvP1y5e/XOqgX33A==, mapNumber=null, fund=null)}, authors=[Author(id=1281683245133697366, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281683242591949133, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=zengdalin@sdjzu.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281683245209194840, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281683242591949133, authorId=1281683245133697366, language=EN, stringName=Dalin ZENG, firstName=Dalin, middleName=null, lastName=ZENG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=School of Management and Engineering, Shandong Jianzhu University, Ji'nan Shandong 250101, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281683245276303705, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281683242591949133, authorId=1281683245133697366, language=CN, stringName=曾大林教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=山东建筑大学 管理工程学院，山东 济南 250101, bio={"content":"

曾大林（1981—），男，山东临朐人，博士，教授，主要从事复杂项目管理、项目治理、建筑经济、智能建造、人机交互等方面的研究。E-mail: zengdalin@sdjzu.edu.cn。

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曾大林（1981—），男，山东临朐人，博士，教授，主要从事复杂项目管理、项目治理、建筑经济、智能建造、人机交互等方面的研究。E-mail: zengdalin@sdjzu.edu.cn。

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