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| Extracting Relationship of Agricultural Financial Texts with Attention Mechanism |
Yuemin Wu,Ganggui Ding,Bin Hu( ) |
| College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095, China |
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Abstract [Objective] This paper proposes a new method to extract relations from Chinese texts automatically. [Methods] We retrieved annual reports of 224 listed agricultural companies from 2015 to 2017. Then we adopted the Gated Recurrent Unit algorithm based on double attention mechanism to extract the needed data. [Results] The average accuracy of our model on the agricultural financial dataset reached 78%. Compared with the Recurrent Neural Network algorithm, the average accuracy of the new model increased by about 12%. [Limitations] We only studied data from 224 companies, which needs to be expanded. [Conclusions] The proposed model can effectively extract relationship from agricultural financial texts.
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Received: 24 July 2018
Published: 03 July 2019
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