基于规则模式的瓦斯爆炸事故信息抽取技术
Gas explosion accident information extraction technology based on regular model
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摘要: 目前煤矿瓦斯爆炸事故报告均为文本记录格式，事故的具体原因信息蕴含在非结构化的文本中，且缺乏专业性的事故词典。为解决人工分析事故费时费力、效率低、分析结果易受主观性影响这一问题，客观提取事故原因，以“事故致因24Model”为事故分析的理论基础，以煤矿重特大瓦斯爆炸事故报告为样本库，构建了事故致因词典库；借助信息抽取技术提出了基于规则模式的事故致因信息抽取算法。抽取结果表明：所抽取的致因因素覆盖人工分析的90%，该方法为在非结构化案例库中快速提取事故致因信息提供了理论支持。Abstract: At present, coal mine gas explosion accident reports are in text record format. The specific cause information of the accident is contained in unstructured text, and there is a lack of professional accident dictionary. In order to solve the problem that manual analysis of accidents is time-consuming and laborious, low efficiency, and the analysis results are easily affected by subjectivity, and objectively extract the causes of accidents, we take “24Model of the cause of accident” as the theoretical basis of accident analysis, take the report of serious gas explosion accident in coal mine as the sample database, and construct the dictionary database of accident causes; with the help of information extraction technology, an accident cause information extraction algorithm based on rule pattern is proposed. The extraction results show that the extracted cause factors cover 90% of the manual analysis. This method provides theoretical support for rapid extraction of accident cause information in unstructured case base.
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Keywords:
- coal mine /
- gas explosion accident /
- 24Model /
- information extraction /
- rule mode
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