Development and Application of an Intelligent Moot Court Trial Platform Based on Machine Learning and Natural Language Processing Technology
- DOI
- 10.2991/978-94-6463-230-9_67How to use a DOI?
- Keywords
- AI Law; Judicial Trial; Machine Learning; Natural Language Processing
- Abstract
The continuous penetration of AI technology into the legal industry has changed the structure of the demand for legal talents, and the demand for complex legal talents in the context of AI has been further expanded, but the combination of legal education and new technology is not close enough today. We should make full use of the technical advantages of AI and combine the characteristics of traditional legal education to find a suitable path for future legal higher education reform. As the current legal education is characterized by a single research and teaching method and insufficient training of students’ effective output, it is extremely important to study the use of AI technology to simulate trial teaching to cultivate practical “AI + Law” talents.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jia Wang AU - Xingyu Yuan AU - Yuqing Zhang AU - Pinxiao Guan AU - Hui Zeng AU - Zeyu Wang PY - 2023 DA - 2023/09/04 TI - Development and Application of an Intelligent Moot Court Trial Platform Based on Machine Learning and Natural Language Processing Technology BT - Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) PB - Atlantis Press SP - 558 EP - 564 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-230-9_67 DO - 10.2991/978-94-6463-230-9_67 ID - Wang2023 ER -