Intelligent Sentencing Assistance System based on BERT Model

Authors

  • Yangli Zhu
  • Peimeng Luo

DOI:

https://doi.org/10.62051/9tkmjm47

Keywords:

Intelligent Sentencing Assistance System; BERT Model; Sentencing Prediction; BERT+DNN Model.

Abstract

This paper takes sentencing prediction as the research object, uses deep learning model, and predicts sentencing recommendations combined with specific cases. BERT+DNN model is used to quantify the text of the case information, endow the sentence with certain meaning, and then send data to DNN network to train the classification model so that it can automatically identify the sentencing circumstances in the text of different cases, and put forward sentencing recommendations based on various circumstances.

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References

Hong Wenxing, Hu Zhiqiang, Weng Yang. et al. Automatic construction of case knowledge graphs for judicial cases[J]. Journal of Chinese Information,2020,34(01):34-44.

Qiu Liwei, Guan Weili, Zhang Weijin. An exploration of the BERT language model [J]. Computer Programming Skills and Maintenance,2021, No.427(01):21-23.

Illustrated BERT Model: Building BERT from Scratch - Tencent Cloud Developer Community - Tencent Cloud (tencent.com).

Fan Aman, Wang Yanchuan. An intelligent adjudication method for multitasking legal cases based on BERT model[J]. Microelectronics and Computers,2022,39(09):107-114.

Jiayi Gu. Research on policy condition identification based on BERT model[J]. Science and Technology Perspectives,2020, No.301(07):251-252.

Cheng Long. The problem and way out of artificial intelligence-assisted sentencing[J]. Journal of Northwestern University (Philosophy and Social Science Edition),2021,51(06):163-174.

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Published

12-10-2023

How to Cite

Zhu, Y. and Luo, P. (2023) “Intelligent Sentencing Assistance System based on BERT Model”, Transactions on Computer Science and Intelligent Systems Research, 1, pp. 64–67. doi:10.62051/9tkmjm47.