基于BiLSTM-CRF的航行通告命名实体识别研究  

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

作　　者：项恒[1] 杨明友 李猛 XIANG Heng;YANG Mingyou;LI Meng(College of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China)

机构地区：[1]中国民航大学空中交通管理学院,天津300300

出　　处：《计算机科学》2024年第S02期115-120,共6页Computer Science

基　　金：国家自然科学基金(U1833103).

摘　　要：针对当前国际民航组织对数字航行通告研究仅考虑对文本航行通告环境兼容,而未考虑对数字航行通告环境兼容的问题,提出一种基于BiLSTM-CRF的航行通告命名实体识别模型,以实现文本航行通告中相关实体的自动识别,并为转换数字航行通告提供所需的基本数据。通过构建航行通告语料标记数据集对LSTM,BiLSTM,BiLSTM-CRF 3种模型进行对比实验。实验结果显示,所提模型的精确率、召回率、F 1值分别为95%,95%,95%,验证了其在航行通告领域的有效性,证明本研究可以有效识别航行通告中的重要实体信息。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.

关 键 词：航行通告 命名实体识别 深度学习 双向长短期记忆网路 条件随机场 

分 类 号：V355[航空宇航科学与技术—人机与环境工程] TP391[自动化与计算机技术—计算机应用技术]