计算机与现代化Issue(3)：61-66,71,7.DOI:10.3969/j.issn.1006-2475.2024.03.010
面向飞机故障文本的信息抽取
Information Extraction for Aircraft Fault Text
摘要
Abstract
In view of the problems of large workload,low efficiency and high cost of manual extraction of aircraft fault informa-tion,a method of information extraction based on domain dictionary,rules and BiGRU-CRF model is proposed.Combining the characteristics of aircraft domain knowledge,domain dictionary and template rules are constructed based on aircraft fault text in-formation,and semantic labeling of fault information is carried out.The BiGRU-CRF deep learning model is used for named en-tity recognition.BiGRU obtaines the semantic relationship of context,and CRF decodes and generates the entity label sequence.The experimental results show that the information extraction method based on domain dictionary,rules and BiGRU-CRF model has an accuracy of 95.2%,which verifies the effectiveness of the method.It can accurately identify the key words in the aircraft fault text,such as time,aircraft type,fault part name,fault part manufacturer and other information.At the same time,accord-ing to the domain dictionary and rules to correct the recognition results,effectively improves the efficiency and accuracy of infor-mation extraction,and solves the problem of traditional entity extraction model long-term dependence on manual features.关键词
故障信息/信息抽取/命名实体识别/BiGRU-CRF/领域词典Key words
fault information/information extraction/named entity recognition/BiGRU-CRF/domain dictionary分类
信息技术与安全科学引用本文复制引用
乔璐,孙有朝,吴红兰..面向飞机故障文本的信息抽取[J].计算机与现代化,2024,(3):61-66,71,7.基金项目
国家自然科学基金委员会-中国民用航空局民航联合研究基金资助项目(U2033202,U1333119) （U2033202,U1333119）
国家自然科学基金资助项目(52172387) （52172387）
