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Study of agricultural finance policy information extraction based on ELECTRA-BiLSTM-CRF

Airong Yang

Airong Yang

College of Economics and Management, Xinjiang Agricultural UniversityChina
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Yang, Airong
 and 
Yong Xia

Yong Xia

College of Economics and Management, Xinjiang Agricultural UniversityChina
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Xia, Yong
  
Dec 12, 2022
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Published Online: Dec 12, 2022
Page range: 2541 - 2550
Received: Jul 11, 2022
Accepted: Nov 19, 2022
DOI: https://doi.org/10.2478/amns.2021.2.00307
Keywords
© 2023 Airong Yang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

General framework of information extraction programme for agricultural finance policy. CRF, conditional random field
General framework of information extraction programme for agricultural finance policy. CRF, conditional random field

Fig. 2

Agricultural finance policy information extraction model architecture. CRF, conditional random field
Agricultural finance policy information extraction model architecture. CRF, conditional random field

Fig. 3

ELECTRA model structure. MLM, Masked Language Model
ELECTRA model structure. MLM, Masked Language Model

Fig. 4

Training of different models. CRF, conditional random field
Training of different models. CRF, conditional random field

Fig. 5

Testing of different models. CRF, conditional random field
Testing of different models. CRF, conditional random field

Fig. 6

Evaluation results. CRF, conditional random field
Evaluation results. CRF, conditional random field
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Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other
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