使用文本挖掘和多层次关联规则来处理和分析中国的事件报告
Yuqian Zhu1, Huimin Liao1, Dengchi Huang2
1School of Resources and Safety Engineering, Central South University, Changsha 410006, China.
Accident; analysis and prevention
|July 28, 2023
概括
通过使用文本挖掘和多层次关联规则分析中国事件报告,可以发现关键的安全模式. 这种方法通过识别事故和近乎事故的趋势和有效的纠正策略来加强安全管理.
科学领域:
- 安全科学安全科学 安全科学
- 数据挖掘 数据挖掘
- 自然语言处理自然语言处理.
背景情况:
- 目前对事件报告的分析依赖于专家的经验,导致对轻微事件和近乎事故的分析不足.
- 这种依赖专业知识和忽略轻微事故限制了全面的安全改进战略.
- 需要有效的数据驱动方法来分析事故报告并提取可操作的安全见解.
研究的目的:
- 建议使用文本挖掘和多层次关联规则来构建中国事件报告的框架.
- 识别关键事件模式,分析趋势,指导安全管理策略.
- 通过中国建筑行业的案例研究来证明框架的实用性.
主要方法:
- 开发了一个使用TextRank和中国报告的域相关性的模式提取工作流.
- 应用概念层次来建立风险因素之间的分类学关系.
- 利用多层次关联规则挖掘用于全面的模式识别和分析.
主要成果:
- 该框架有效地结构化了事件数据,并确定了重大事件模式.
- 分析揭示了事故的时间特征和安全措施的有效性.
- 差点失误事件被强调为学习和提高安全绩效的关键.
结论:
- 拟议的框架为分析中国事件报告提供了一种有效的方法,超越了专家的依赖.
- 多层次关联规则为事件模式和安全趋势提供了更深入的见解.
- 利用近距离撞击数据对于积极的安全管理和政策制定至关重要.
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