【摘要】 城镇自建房安全事故频发对公共安全构成严重威胁。为提高城镇自建房安全风险控制水平,有效减少城镇自建房安全事故发生,通过文本挖掘技术对城镇自建房安全事故案例进行分析,识别城镇自建房安全风险影响因素。将DEMATEL模型与Apriori算法结合,确定影响因素的重要性和因果属性。在此基础上引入ISM,建立影响因素层级递阶结构。结果表明:建筑结构缺陷、操作违规、资质缺失等影响因素是导致城镇自建房安全风险发生的关键因素;制度体系缺陷、监督与执行失效和缺乏教育培训影响因素是导致安全风险发生的根本因素。研究结果可为利益相关方采取针对性措施提供参考,也可为城镇自建房安全风险管控提供一定的依据。更多还原

【Abstract】 The frequent occurrence of safety accidents in urban self-built houses poses a serious threat to public safety.To improve the level of safety risk control for urban self-built houses and effectively reduce the occurrence of such safety accidents, this research analyzed cases of safety accidents in urban self-built houses through text mining technology to identify the influencing factors of safety risks in urban self-built houses. By combining the DEMATEL model with the Apriori algorithm, the importance and causal attributes of the influencing factors were determined. On this basis,the ISM was introduced to establish a hierarchical recursive structure of the influencing factors. The results show that:defects in building structures, operational violations, and lack of qualifications are key factors leading to safety risks in urban self-built houses; defects in the institutional system, failure in supervision and enforcement, and lack of education and training are fundamental factors causing safety risks. The research results can provide a reference for relevant parties to take targeted measures and also offer a basis for the safety risk management and control of urban self-built houses.更多还原