Analysis of Criminal Case Judgment Documents Based on Deep Learning

DOI

10.2991/acaai-18.2018.61How to use a DOI?

Keywords

convolutional neural network; multiple nuclear convolution; criminal case verdict document; prediction of sentencing interval

Abstract

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.

Copyright

© 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/).

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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  -