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- Title
Methods of incorporating common element characteristics for law article prediction.
- Authors
Hou, Yifan; Cheng, Ge; Zhang, Yun; Zhang, Dongliang
- Abstract
Law article prediction is a task of predicting the relevant laws and regulations involved in a case according to the description text of the case, and it has broad application prospects in improving judicial efficiency. In the existing research work, researchers often only consider a single case, employing the neural network method to extract features for prediction, which lack the mining of related and common element information between different data. In order to solve this problem, we propose a law article prediction method that integrates the characteristics of common elements. It can effectively utilize the co-occurrence information of the training data, fully mine the relevant common elements between cases, and fuse local features. Experiments show that our method performs well.
- Subjects
ARTIFICIAL neural networks; DATA mining; JUDICIAL process; FEATURE extraction; MACHINE learning
- Publication
Artificial Intelligence & Law, 2024, Vol 32, Issue 2, p487
- ISSN
0924-8463
- Publication type
Article
- DOI
10.1007/s10506-023-09359-6