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Methods of incorporating common element characteristics for law article prediction

Methods of incorporating common element characteristics for law article prediction 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence and Law Springer Journals

Methods of incorporating common element characteristics for law article prediction

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References (15)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
ISSN
0924-8463
eISSN
1572-8382
DOI
10.1007/s10506-023-09359-6
Publisher site
See Article on Publisher Site

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.

Journal

Artificial Intelligence and Law – Springer Journals

Published: Apr 24, 2023

Keywords: Law article prediction; Text classification; Feature fusion; Graph neural network; Attention mechanism

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