A Weakly-Supervised Method for Named Entity Recognition of Agricultural Knowledge Graph-Reference-Cited by-同舟云学术

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A Weakly-Supervised Method for Named Entity Recognition of Agricultural Knowledge Graph

Published:2023 Issue:1 Volume:37 Page:833-848
ISSN:1079-8587
Container-title:Intelligent Automation & Soft Computing
language:en
Short-container-title:

Author:

Wang Ling,Jiang Jingchi,Song Jingwen,Liu Jie

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

https://www.techscience.com/iasc/v37n1/52663/pdf

Reference38 articles.

1. CCG supertagging via bidirectional LSTM-CRF neural architecture;Kadari;Neurocomputing,2018

2. A conditional random field word segmented for sighan bakeoff;Tseng,2005

3. Neural architectures for named entity recognition;Lample,2016

4. Character-based LSTM-CRF with radical-level features for Chinese named entity recognition;Dong,2016

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. VEG-MMKG: Multimodal knowledge graph construction for vegetables based on pre-trained model extraction;Computers and Electronics in Agriculture;2024-11

2. Based on BERT-wwm for Agricultural Named Entity Recognition;Agronomy;2024-06-04

3. GlyReShot: A glyph-aware model with label refinement for few-shot Chinese agricultural named entity recognition;Heliyon;2024-06

4. Evolution and emerging trends of named entity recognition: Bibliometric analysis from 2000 to 2023;Heliyon;2024-05

5. Veg-Mmkg: Multimodal Knowledge Graph Construction for Vegetables Based On Pre-Trained Model Extraction;2024

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