Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (11A): 240300148-6.doi: 10.11896/jsjkx.240300148

• Intelligent Computing • Previous Articles     Next Articles

Study on Named Entity Recognition of NOTAM Based on BiLSTM-CRF

XIANG Heng, YANG Mingyou, LI Meng   

  1. College of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China
  • Online:2024-11-16 Published:2024-11-13
  • About author:XIANG Heng,born in 1975,master,associate professor.His main research interests include air traffic control human factors and aeronautical information management.
  • Supported by:
    National Natural Science Foundation of China(U1833103).

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Abstract: Aiming at the problem that the current research of International Civil Aviation Organization in digital NOTAMs,which only considers the compatibility with the environment of textual NOTAMs,but not digital NOTAMs,a named entity recognition model for NOTAMs based on BiLSTM-CRF is proposed to realise the automatic recognition of relevant entities in textual NOTAMs and to provide the necessary basic data for the conversion of digital NOTAMs.Comparative experiments are carried out by constructing a NOTAM corpus tagged dataset in three models,LSTM,BiLSTM and BiLSTM-CRF,and the experimental results show that the precision,recall and F1 value of the proposed method is 95%,95% and 95%,respectively,which verifies the effectiveness of the proposed method in the field of NOTAMs and proves that this study can effectively obtain the important entity information in NOTAMs.

Key words: NOTAM, Name entity recognition, Deep learning, BiLSTM, CRF

CLC Number: 

  • V355
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