Named Entity Recognition of Chinese Crop Diseases and Pests Based on RoBERTa-wwm with Adversarial Training
文献类型：期刊论文
| 作者 | Liang, Jianqin; Li, Daichao; Lin, Yiting; Wu, Sheng; Huang, Zongcai2 |
| 刊名 | AGRONOMY-BASEL
 |
| 出版日期 | 2023-03-01 |
| 卷号 | 13期号:3页码:941 |
| 关键词 | crop diseases and pests named entity recognition deep learning pre-training language model adversarial training |
| DOI | 10.3390/agronomy13030941 |
| 文献子类 | Article |
| 英文摘要 | This paper proposes a novel model for named entity recognition of Chinese crop diseases and pests. The model is intended to solve the problems of uneven entity distribution, incomplete recognition of complex terms, and unclear entity boundaries. First, a robustly optimized BERT pre-training approach-whole word masking (RoBERTa-wwm) model is used to extract diseases and pests' text semantics, acquiring dynamic word vectors to solve the problem of incomplete word recognition. Adversarial training is then introduced to address unclear boundaries of diseases and pest entities and to improve the generalization ability of models in an effective manner. The context features are obtained by the bi-directional gated recurrent unit (BiGRU) neural network. Finally, the optimal tag sequence is obtained by conditional random fields (CRF) decoding. A focal loss function is introduced to optimize conditional random fields (CRF) and thus solve the problem of unbalanced label classification in the sequence. The experimental results show that the model's precision, recall, and F1 values on the crop diseases and pests corpus reached 89.23%, 90.90%, and 90.04%, respectively, demonstrating effectiveness at improving the accuracy of named entity recognition for Chinese crop diseases and pests. The named entity recognition model proposed in this study can provide a high-quality technical basis for downstream tasks such as crop diseases and pests knowledge graphs and question-answering systems. |
| WOS研究方向 | Agriculture ; Plant Sciences |
| WOS记录号 | WOS:000952930500001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200820]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Fuzhou Univ, Acad Digital China Fujian, Fuzhou 350116, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liang, Jianqin,Li, Daichao,Lin, Yiting,et al. Named Entity Recognition of Chinese Crop Diseases and Pests Based on RoBERTa-wwm with Adversarial Training[J]. AGRONOMY-BASEL,2023,13(3):941. |
| APA | Liang, Jianqin,Li, Daichao,Lin, Yiting,Wu, Sheng,&Huang, Zongcai.(2023).Named Entity Recognition of Chinese Crop Diseases and Pests Based on RoBERTa-wwm with Adversarial Training.AGRONOMY-BASEL,13(3),941. |
| MLA | Liang, Jianqin,et al."Named Entity Recognition of Chinese Crop Diseases and Pests Based on RoBERTa-wwm with Adversarial Training".AGRONOMY-BASEL 13.3(2023):941. |
入库方式： OAI收割
来源：地理科学与资源研究所
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