| dc.contributor | 資訊系 | - |
| dc.creator (作者) | 劉昭麟 | - |
| dc.creator (作者) | Liu, Chao-Lin;Huang, Ho Chien | - |
| dc.date (日期) | 2025-05 | - |
| dc.date.accessioned | 19-May-2025 11:44:35 (UTC+8) | - |
| dc.date.available | 19-May-2025 11:44:35 (UTC+8) | - |
| dc.date.issued (上傳時間) | 19-May-2025 11:44:35 (UTC+8) | - |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/157014 | - |
| dc.description.abstract (摘要) | This study proposes a new approach for identifying relevant articles based on transactions or occurrences. The primary objective of this study is to determine which legal articles can serve as claims or counterarguments given a specific transaction or a particular occurrence. To achieve this, we analyze judicial judgments and assess the relevance between the predicted and actual cited articles. Based on empirical observations from preliminary research, we identify candidate articles using two main approaches: a nearest-neighbor approach and a distance-based method. Furthermore, we investigate we can use hybrid method to optimize the performance and provide a simple implementation of our work on recommendation system, which has the potential for widespread application among both the general public and law firms. | - |
| dc.format.extent | 117 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | JSAI International Symposium on Artificial Intelligence, Lecture Notes in Computer Science, Springer Nature, Vol.15692, pp.161–175 | - |
| dc.title (題名) | Nearest-neighbor search or distance-based search, which is better for finding relevant articles? | - |
| dc.type (資料類型) | conference | - |
| dc.identifier.doi (DOI) | 10.1007/978-981-96-7071-0_11 | - |
| dc.doi.uri (DOI) | https://doi.org/10.1007/978-981-96-7071-0_11 | - |
