Abstract
Nowadays, intelligent retrieval systems in law are vital in facilitating legal research and providing access to vast legal information. These systems allow users to search for legal information more efficiently and accurately. This paper investigates retrieval systems, their technological advancements, and their impact on legal research. The experimental results show that the proposed method is emerging to apply for analysis queries of practical law cases and extract suitable information from legal documents. It also discusses the challenges associated with law retrieval systems and explores future research directions to improve them.
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Notes
- 1.
baohiemxahoi.gov.vn - This website provides information on social insurance policies, social insurance duties and procedures related to social insurance.
- 2.
thuvienphapluat.vn - Thuvienphapluat is a Vietnamese website that provides online legal documents of Vietnam and related legal documents.
References
National Assembly: Labor on Employment 2013, No. 38/2013/QH13 (2013)
National Assembly: Labor Code 2019, No. 45/2019/QH14 (2019)
Bui, T.V., Tran, O.T., Le-Hong, P.: Improving sequence tagging for Vietnamese text using transformer-based neural models. CoRR abs/2006.15994 (2020). https://arxiv.org/abs/2006.15994
Dale, R.: Law and word order: NLP in legal tech. Nat. Lang. Eng. 25(1), 211–217 (2019)
Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, Minneapolis, Minnesota, June 2019
Fernández-Barrera, M., Sartor, G.: The legal theory perspective: doctrinal conceptual systems vs. computational ontologies. In: Sartor, G., Casanovas, P., Biasiotti, M., Fernández-Barrera, M. (eds.) Approaches to Legal Ontologies. Law, Governance and Technology Series, vol. 1, pp. 15–47. Springer, Dordrecht (2011). https://doi.org/10.1007/978-94-007-0120-5_2
Vietnam Government: Decree on Detailing Unemployment Insurance of the Law on employment - No. 28/2015/ND-CP (2015)
Vietnam Government: Decree on detailing and guiding the implementation of a number of articles of the labour code regarding working conditions and labour relations, No. 145/2020/ND-CP (2020)
Le, T.A.T., Vodden, K., Wu, J., Atiwesh, G.: Policy responses to the covid-19 pandemic in Vietnam. Int. J. Environ. Res. Public Health 18(2), 559 (2021)
Mirończuk, M.M.: The BigGrams: the semi-supervised information extraction system from html: an improvement in the wrapper induction. Knowl. Inf. Syst. 54(3), 711–776 (2018)
Ngo, H., Nguyen, T., Nguyen, D., et al.: AimeLaw at ALQAC 2021: enriching neural network models with legal-domain knowledge. In: 2021 13th International Conference on Knowledge and Systems Engineering (KSE). IEEE (2021)
Nguyen, D.Q., Nguyen, A.T.: PhoBERT: pre-trained language models for Vietnamese. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 1037–1042 (2020)
Nguyen, H., Tran, T.V., Pham, X.T., Huynh, A.: Ontology-based integration of knowledge base for building an intelligent searching chatbot. Sens. Mater. 33(9), 3101–3123 (2021)
Nguyen, H.D., Pham, V.T., Le, T.T., Tran, D.H.: A mathematical approach for representing knowledge about relations and its application. In: Proceedings of 7th International Conference on Knowledge and Systems Engineering (KSE 2015), pp. 324–327. IEEE (2015)
Nguyen, T.H., Nguyen, H.D., Pham, V.T., Tran, D.A., Selamat, A.: Legal-Onto: an ontology-based model for representing the knowledge of a legal document. In: Proceedings of 17th Evaluation of Novel Approaches to Software Engineering (ENASE 2022), Online streaming, pp. 426–434 (2022)
de Oliveira Rodrigues, C.M., de Freitas, F.L.G., Barreiros, E.F.S., de Azevedo, R.R., de Almeida Filho, A.T.: Legal ontologies over time: a systematic mapping study. Exp. Syst. Appl. 130, 12–30 (2019)
Pham, V.T., Nguyen, H.D., Le, T., et al.: Ontology-based solution for building an intelligent searching system on traffic law documents. In: Proceedings of 15th International Conference on Agents and Artificial Intelligence (ICAART 2023), Lisbon, Portugal, pp. 217–224 (2023)
Qaiser, S., Ali, R.: Text mining: use of TF-IDF to examine the relevance of words to documents. Int. J. Comput. Appl. 181(1), 25–29 (2018)
Reimers, N., Gurevych, I.: Sentence-BERT: sentence embeddings using Siamese BERT-networks. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (2019). https://arxiv.org/abs/1908.10084
Robertson, S., Zaragoza, H.: The probabilistic relevance framework: BM25 and beyond. Foundations Trends Inf. Retrieval 3, 333–389 (2009). https://doi.org/10.1561/1500000019
Trinh, N.T.T.: Impact of the Covid-19 on the labor market in Vietnam. Int. J. Health Sci. 6, 6355–6367 (2022)
Villata, S., Araszkiewicz, M., Ashley, K., et al.: Thirty years of artificial intelligence and law: the third decade. Artif. Intell. Law 30, 561–591 (2022)
Vu, T., Nguyen, D.Q., Nguyen, D.Q., Dras, M., Johnson, M.: VnCoreNLP: a Vietnamese natural language processing toolkit. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pp. 56–60. Association for Computational Linguistics, New Orleans, Louisiana, June 2018. https://doi.org/10.18653/v1/N18-5012. https://aclanthology.org/N18-5012
Zhao, G., Liu, Y., Erdun, E.: Review on intelligent processing technologies of legal documents. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds.) Artificial Intelligence and Security: 8th International Conference, ICAIS 2022, Qinghai, China, 15–20 July 2022, Proceedings, Part I, pp. 684–695. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-06794-5_55
Zhong, H., Xiao, C., Tu, C., et al.: How does NLP benefit legal system: a summary of legal artificial intelligence. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (COLING 2020), pp. 5218–5230. Association for Computational Linguistics (2020)
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Le, H.H. et al. (2023). Intelligent Retrieval System on Legal Information. In: Nguyen, N.T., et al. Intelligent Information and Database Systems. ACIIDS 2023. Lecture Notes in Computer Science(), vol 13995. Springer, Singapore. https://doi.org/10.1007/978-981-99-5834-4_8
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