基于文本聚类的煤矿安全事故类型分析

Analysis of Coal Mine Safety Accident Type Based on Text Clustering

为减少煤矿安全事故发生的频率,充分利用现有的煤矿安全事故数据,分析事故发生的特点,探寻各事故之间存在的潜在规律,对我国煤矿企业管理者实施针对性的管理措施有重要意义。本研究选取中国煤矿安全生产网2016-2020年煤矿安全事故描述数据,利用VSM模型实现文本向量化,运用文本聚类识别数据中存在的主要事故类型,并采用卡方统计方法提取与类别相关的特征词用以描述聚类结果。结果表明,文本聚类与卡方统计相结合能很好地识别煤矿安全事故描述数据的事故类型及特点;事故预防应该重点抓人的因素,以提高煤矿生产人员的安全意识,完善煤矿管理制度工作为主;其次对于事故常发的位置,做好重点防范工作。

Absrtact:In order to reduce the frequency of coal mine safety accidents,make full use of the existing coal mine safety accident data,analyze the characteristics of the accidents,and explore the potentiallaws between the accidents,It is of great significance to implement targeted management measures formanagers of coal mining enterprises in China.Based on the description data of coal mine safety accidents in China Coal Mine Safety production Network from 2016 to 2020,the text vectorization is realized by using VSM model,and the main accident types in the data are identified by text clustering.Theclass-related feature words are extracted by chi-square statistical method to describe the clustering results.The results show that text clustering and chi-square system The combination of calculation canwell identify the accident types and characteristics of coal mine safety accident description data,andthe accident prevention should focus on the factors of people,so as to improve the safety consciousnessof coal mine production personnel and improve the coal mine management system.