To enrich the safety knowledge in the field of construction industry,the unsafe behaviors of workers are mined and discovered from accident texts.This paper took the unsafe behavior related to personal protective equipment(PPE)as an example,and this kind of unsafe behavior was automatically extracted from accident texts using a rule-based natural language processing method.195 construction accident investigation reports were collected from government websites to form a text mining corpus.The lexical analysis and dependency parsing of the texts were carried out through the Language Technology Platform(LTP)of Harbin Institute of Technology.The 11 extraction rules of the unsafe behavior related to PPE were constructed and the extraction process is determined.Then,another 427 construction accident investigation reports collected by web crawlers were used as examples to automatically extract the unsafe behavior related to PPE according to the extraction process.The results show that the average extraction accuracy is 94.70%and recall rate is 67.57%.The study can provide a theoretical inspiration and practical path for knowledge discovery in construction accident texts.
关键词
知识发现/事故文本/PPE类不安全行为/自然语言处理
Key words
knowledge discovery/accident texts/PPE related unsafe behaviors/natural language processing
维普
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