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Research on the Financial Event Extraction Method Based on Fin-BERT Cover
By: Jing He and  Yongyong Sun  
Open Access
|Dec 2024

Figures & Tables

Figure 1.

Model framework

Figure 2.

The trained model of Fin-Bert

Figure 3.

RAAT structure

Figure 4.

Types of Events Extracted Resulting F1 Values

experimental extraxtion of chfinann datasets

PRF1
Doc2EDAG80.370.577.5
GIT82.378.480.3
PTPCG88.269.179.4
Fin-RAAT84.079.981.9

comparison of event extraction experiment results in chfinann datasets

F1
SingleMultiAll
Doc2EDAG81.067.477.5
GIT87.672.380.3
PTPCG88.269179.4
Fin-RAAT87.975.381.9

datasets information

Training dataValidation dataTest dataEvent types
ChFinAnn25632320432045
Duee-fin70151171About 350013

duee-fin datasets

DevOnline test
PRF1PRF1
Doc2EDAG73.759.866.067.151.358.1
GIT75.461.467.770.346.055.6
PTPCG71.061.766.066.754.660.0
Fin-RAAT76.171.373.070.356.162.8

experimental enviroment

Hardware InformationConfigure
Operating systemWindows 10
Internal storage32GB
CPUAMD R9-5900HX
Video cardRTX-3080-LAPTOP
Memory16GB
Exploitation environmentPython 3.7
Language: English
Page range: 67 - 74
Published on: Dec 31, 2024
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2024 Jing He, Yongyong Sun, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.