计算机与控制工程 |
|
|
|
|
基于法条知识的事理型类案检索方法 |
李林睿1( ),王东升2,*( ),范红杰2 |
1. 浙江大学 光华法学院,浙江 杭州 310008 2. 中国政法大学 法治信息管理学院,北京 102249 |
|
Fact-based similar case retrieval methods based on statutory knowledge |
Linrui LI1( ),Dongsheng WANG2,*( ),Hongjie FAN2 |
1. Guanghua Law School, Zhejiang University, Hangzhou 310008, China 2. School of Information Management for Law, China University of Political Science and Law, Beijing 102249, China |
1 |
BHATTACHARYA P, GHOSH K, PAL A, et al. Methods for computing legal document similarity: a comparative study [EB/OL]. (2020-04-26)[2023-08-10]. https://arxiv.org/pdf/2004.12307.
|
2 |
WAGH R S, ANAND D Legal document similarity: a multi-criteria decision-making perspective[J]. PeerJ Computer Science, 2020, 6: e262
doi: 10.7717/peerj-cs.262
|
3 |
TRAN V, NGUYEN M L, SATOH K. Building legal case retrieval systems with lexical matching and summarization using a pre-trained phrase scoring model [C]// Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law . [S.l.]: Association for Computing Machinery, 2019: 275–282.
|
4 |
JIANG J Y, ZHANG M, LI C, et al. Semantic text matching for long-form documents [C]// The World Wide Web Conference . [S.l.]: Association for Computing Machinery, 2019: 795–806.
|
5 |
SHAO Y, MAO J, LIU Y, et al. BERT-PLI: modeling paragraph-level interactions for legal case retrieval [C]// International Joint Conference on Artificial Intelligence . Yokohama: [s.n.], 2020: 3501–3507.
|
6 |
ALI B, MORE R, PAWAR S, et al. Prior case retrieval using evidence extraction from court judgements [C]// The Fifth Workshop on Automated Semantic Analysis of Information in Legal Text . São Paulo: [s.n.], 2021: 1–11.
|
7 |
MA Y, SHAO Y, WU Y, et al. LeCaRD: a legal case retrieval dataset for Chinese law system [C]// Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval . [S.l.]: Association for Computing Machinery, 2021: 2342–2348.
|
8 |
YOSHIOKA M, KANO Y, KIYOTA N, et al. Overview of japanese statute law retrieval and entailment task at COLIEE-2018[C]// Proceedings of the Twelfth International Workshop on Juris-Informatics . Yokohama: [s.n.], 2018: 117–128
|
9 |
赵京胜, 宋梦雪, 高祥, 等 自然语言处理中的文本表示研究[J]. 软件学报, 2022, 33 (1): 102- 128 ZHAO Jingsheng, SONG Mengxue, GAO Xiang, et al Research on text representation in natural language processing[J]. Journal of Software, 2022, 33 (1): 102- 128
|
10 |
WEI L, ZHOU C, SU R, et al PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning[J]. Bioinformatics, 2019, 35 (21): 4272- 4280
doi: 10.1093/bioinformatics/btz246
|
11 |
LEE H Y, HUANG J B, SINGH M, et al. Unsupervised representation learning by sorting sequences [C]// Proceedings of the IEEE International Conference on Computer Vision . Venice: IEEE, 2017: 667–676.
|
12 |
SUK H I, SHEN D. Deep learning-based feature representation for AD/MCI classification [C]// International Conference on Medical Image Computing and Computer Assisted Intervention . [S.l.]: Springer. 2013: 583–590.
|
13 |
李松, 舒世泰, 郝晓红, 等 融合文本描述和层次类型的知识表示学习方法[J]. 浙江大学学报: 工学版, 2023, 57 (5): 911- 920 LI Song, SHU Shitai, HAO Xiaohong, et al Knowledge representation learning method integrating textual description and hierarchical type[J]. Journal of Zhejiang University: Engineering Science, 2023, 57 (5): 911- 920
|
14 |
ZHONG H, ZHOU J, QU W, et al. An element-aware multi-representation model for law article prediction [C]// Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing . [S.l.]: Association for Computational Linguistics, 2020: 6663–6668.
|
15 |
LI L, SHI X, DING Y, et al. Event logic graph construction for event mining [C]// Journal of Physics: Conference Series . Beijing: IOP, 2021, 2037: 012135.
|
16 |
DING X, LI Z, LIU T, et al. ELG: an event logic graph [EB/OL]. (2019-08-07)[2023-08-10]. https://arxiv.org/pdf/1907.08015.
|
17 |
DU L, DING X, XIONG K, et al. ExCAR: event graph knowledge enhanced explainable causal reasoning [C]// Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing . [S.l.]: Association for Computational Linguistics, 2021: 2354–2363.
|
18 |
WANG Z. Legal element-oriented modeling with multi-view contrastive learning for legal case retrieval [C]// International Joint Conference on Neural Networks . Padua: IEEE, 2022: 1–10.
|
19 |
SHAO Y, WU Y, LIU Y, et al Understanding relevance judgments in legal case retrieval[J]. ACM Transactions on Information Systems, 2023, 41 (3): 1- 32
|
20 |
HU W, ZHAO S, ZHAO Q, et al BERT_LF: a similar case retrieval method based on legal facts[J]. Wireless Communications and Mobile Computing, 2022, 2022: 1- 9
|
21 |
NIGAM S K, GOEL N, BHATTACHARYA A. Nigam@COLIEE-22: legal case retrieval and entailment using cascading of lexical and semantic-based models [C]// New Frontiers in Artificial Intelligence . [S.l.]: Springer, 2023: 96–108.
|
22 |
TAN M, JIANG J, DAI B T A BERT-based two-stage model for Chinese chengyu recommendation[J]. ACM Transactions on Asian and Low-Resource Language Information Processing, 2021, 20 (6): 1- 18
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|