Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (11): 265-270.DOI: 10.3778/j.issn.1002-8331.1902-0257

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Research on Causality Extraction of Civil Aviation Accident

WANG Hong, ZHU Han, LIN Haizhou   

  1. School of Computer Science & Technology, Civil Aviation University of China, Tianjin 300300, China
  • Online:2020-06-01 Published:2020-06-01



  1. 中国民航大学 计算机科学与技术学院,天津 300300


Previous research on causality analysis of civil aviation accidents is mainly based on probability and statistic methods, lacking of the analysis based on the whole process of accident occurrence. In order to excavate the process of aviation accidents, the causality extraction method is studied. The causality is divided into explicit causality and implicit causality, and the pattern matching method is applied to get explicit causality, which reaches 87.72% in precise rate. While the improved bidirectional long short-term memory networks with self-attention mechanism is adopted for implicit causality extraction. Compared to the baseline method, the F measure of this method on public dataset and aviation dataset is increased by nearly 6% and 10%, respectively. The proposed approach is applied to the text dataset of world aviation safety accident investigation reports. On the basis of the effectively extraction of causality, causality graph for each accident is generated, which provides the data and method to civil aviation accident’s comprehensive analysis and scene reappearance.

Key words: civil aviation accident, relation extraction, explicit causality, implicit causality, pattern matching, self-attention mechanism



关键词: 航空安全事故, 关系抽取, 显式因果关系, 隐式因果关系, 模式匹配, 自注意力机制