Analysis of Criminal Case Judgment Documents Based on Deep Learning
- 10.2991/acaai-18.2018.61How to use a DOI?
- convolutional neural network; multiple nuclear convolution; criminal case verdict document; prediction of sentencing interval
In recent years, along with the improvement of population quality and the advancement of the rule of law society, the market for legal services in the middle and low-end markets has continued to expand, and legal advice has become widespread in daily life. In the process of legal services, the legal provisions play an important role in the lawyer's decision-making. Meanwhile, the historical cases can help the lawyers and the parties to draw lessons from similar cases. However, with the increasing number of judicial documents, it is becoming increasingly difficult to summarize and learn from history. Therefore, this paper proposes a sentencing interval prediction model of criminal cases based on convolutional neural network, and through the method of multi-core convolution, greatly enhances the generalization ability and prediction performance of the model. The experimental analysis of real criminal case verdict verifies that the model is more effective than other classification prediction algorithms.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Jinbo Han AU - Dakui Li AU - Nanhai Yang AU - Zhu Liu AU - Qiong Nan PY - 2018/03 DA - 2018/03 TI - Analysis of Criminal Case Judgment Documents Based on Deep Learning BT - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018) PB - Atlantis Press SP - 261 EP - 264 SN - 1951-6851 UR - https://doi.org/10.2991/acaai-18.2018.61 DO - 10.2991/acaai-18.2018.61 ID - Han2018/03 ER -