| dc.contributor | 資訊系 | |
| dc.creator (作者) | 劉昭麟 | |
| dc.creator (作者) | Liu, Chao-Lin;Wang, JingZi | |
| dc.date (日期) | 2022-12 | |
| dc.date.accessioned | 30-Nov-2023 11:26:37 (UTC+8) | - |
| dc.date.available | 30-Nov-2023 11:26:37 (UTC+8) | - |
| dc.date.issued (上傳時間) | 30-Nov-2023 11:26:37 (UTC+8) | - |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/148301 | - |
| dc.description.abstract (摘要) | Legal judgement prediction is a critical application in the law and AI field, and has received great attention in recent years. In this paper, we focus on the recommendations of applicable law articles for a given criminal case. This is a multi-label problem in nature, since it is common for a sequence of criminal activities to violate the law in many aspects. We compare two different strategies for identifying the articles. The first one employs only the Lawformer, which is a Longformer-based model designed specifically for the legal domain, and the second one will combine the applications of the Lawformer with a traditional technique for keyword selection. The experimental results indicate that integrating the deep learning and the traditional methods provide a better result. | |
| dc.format.extent | 109 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Proceedings of 2022 International Conference on Computational Science and Computational Intelligence, American Council on Science and Education, pp.321-322 | |
| dc.subject (關鍵詞) | Multi-label classification; deep learning; Natural language processing; Chinese judicial documents | |
| dc.title (題名) | Intelligent processing of judicial documents based on deep learning | |
| dc.type (資料類型) | conference | |
| dc.identifier.doi (DOI) | 10.1109/CSCI58124.2022.00064 | |
| dc.doi.uri (DOI) | https://doi.org/10.1109/CSCI58124.2022.00064 | |
