计算机应用与软件2024，Vol.41Issue(6)：223-229,7.DOI:10.3969/j.issn.1000-386x.2024.06.033
基于BERT的农作物命名实体识别模型研究
BERT-BASED NAMED ENTITY RECOGNITION MODEL FOR AGRICULTURAL DOMAINS
摘要
Abstract
With the rapid development of digital agriculture,crop named entity recognition,as the basis of knowledge graph construction in agriculture,is becoming an efficient crop recognition method.Since crop entity recognition presents complex structure,inconsistent entity designations,and multiple confounding factors,which seriously restrict the performance of entity recognition in crop domain,the paper proposes an entity recognition model based on pre-trained language models.BERT was used to encode words in text,bi-directional LSTM was used to obtain the context of each keyword in a sentence,and CRFs was used to capture the dependencies between words.The model was validated with the constructed crop named entity recognition dataset.The experiments demonstrate that the model can effectively recognize crop entities and outperforms the existing entity recognition models.关键词
命名实体识别/BERT预训练语言模型/双向LSTM/农作物Key words
Named entity recognition/BERT Pre-trained language models/Bi-directional long and short-term memory/Crops分类
信息技术与安全科学引用本文复制引用
沈子雷,杜永强..基于BERT的农作物命名实体识别模型研究[J].计算机应用与软件,2024,41(6):223-229,7.基金项目
河南省科技攻关项目(222102110189). （222102110189）
