计算机应用与软件2024，Vol.41Issue(4)：119-128,10.DOI:10.3969/j.issn.1000-386x.2024.04.019
基于深度学习与规则结合的海运货物邮件命名实体识别
NAMED ENTITY RECOGNITION OF SHIPPING CARGO MAIL BASED ON DEEP LEARNING AND RULES
摘要
Abstract
To address the problems such as low recognition accuracy and the difficulty in entity boundary determination in named entity recognition of shipping cargo mails,this paper proposes a named entity recognition model based on deep learning and rules.Based on the model BiLSTM-CRF(bidirectional long short term memory-conditional random field),the deep learning method added word character level features and engaged in the multi-head attention mechanisms to obtain the long-distance dependence of texts.The rule matching method made corresponding rules according to the characteristics of domain entities to complete the recognition.According to the characteristics of shipping cargo mails,corpus was marked and divided into five categories:cargo name,quantity,loading and discharge port,laycan and commission.A series of comparative experiments were conducted in self-built shipping cargo text corpus.The experimental results show that the F1 value reaches 79.3％in the field of shipping cargo mails entity recognition.关键词
命名实体识别/海运货物邮件/多头注意力机制/字符级特征/规则匹配Key words
Named entity recognition/Shipping cargo mail/Multi-head attention mechanism/Character-level features/Rule matching分类
信息技术与安全科学引用本文复制引用
滕俊凯,张俊..基于深度学习与规则结合的海运货物邮件命名实体识别[J].计算机应用与软件,2024,41(4):119-128,10.基金项目
国家自然科学基金项目(61976032). （61976032）
