基于文本聚类的煤矿安全隐患类型挖掘研究

Research on mining types of safety hidden dangers in coal mine based on text clustering

为提升煤矿安全管理者对隐患数据的理解和处理能力,提高隐患排查治理工作水平,将文本聚类方法运用于煤矿企业历史安全隐患记录数据的挖掘分析,并采用卡方统计量提取与类别关联度高的特征词描述聚类结果,研究历史隐患数据中记录的主要隐患的类型及特点。结果表明:文本聚类与卡方统计相结合,能够有效识别煤矿安全隐患数据中记录的主要隐患类型及特点;隐患排查治理工作应以数量多的隐患类型作为排查侧重点,根据隐患类型的特点制定相应的治理措施,以改善隐患排查治理工作的针对性和有效性。

In order to enhance the ability of coal mine safety administrators to understand and process hidden danger data, and improve the work of hidden danger investigation and management, the text clustering method was applied to mining and analyzing the data of historical safety hazards records of coal mining enterprises.The chi-square statistics was used to extract feature words, and the feature words with high degree of correlation with category were used to describe the clustering results. The main types and characteristics of hidden dangers recorded in historical data were studied. The results show that the combination of text clustering and chi-square statistics could identify the types and characteristics of the main hidden dangers recorded in the data on coal mine safety hazards and that the serctor in coal mine responsible for investigation and treatment of hidden dangers should focus on the hidden danger types with large numbers, and formulate corresponding treatment measures according to the characteristics of hidden danger types, so as to improve the pertinence and effectiveness of the investigation and treatment of hidden dangers.