Autor(es): Silva, Hugo ; António, Nuno ; Bacao, Fernando
Data: 2022
Identificador Persistente: http://hdl.handle.net/10362/144564
Origem: Repositório Institucional da UNL
Projeto/bolsa: info:eu-repo/grantAgreement/FCT/3599-PPCDT/DSAIPA%2FDS%2F0116%2F2019/PT;
Assunto(s): Precedents retrieval; Rapid review; Automated; Theoretical Computer Science; Computer Science(all); SDG 16 - Peace, Justice and Strong Institutions
Silva, H., António, N., & Bacao, F. (2022). A Rapid Semi-automated Literature Review on Legal Precedents Retrieval. In G. Marreiros, B. Martins, A. Paiva, B. Ribeiro, & A. Sardinha (Eds.), Progress in Artificial Intelligence: 21st EPIA Conference on Artificial Intelligence, EPIA 2022, Lisbon, Portugal, August 31–September 2, 2022, Proceedings (pp. 53-65). (Lecture Notes in Artificial Intelligence; Vol. 13566). Springer, Cham. https://doi.org/10.1007/978-3-031-16474-3_5. Funding Information: This research was supported by a grant from the Portuguese Foundation for Science and Technology (“Fundação para a Ciência e a Tecnologia”) [grant number DSAIPA/DS/0116/2019].
Precedents constitute the starting point of judges’ reasoning in national legal systems. Precedents are also an essential input for case-based reasoning (CBR) methodologies. Although considerable research has been done on CBR applied to legal practice, the precedent retrieval techniques are a relatively new and unexplored field of AI & Law. Only a few works have tested or developed methods for identifying such previous similar cases. This work uses text mining (TM), natural language processing (NLP), and data visualization methods to provide a semi-automated rapid literature review and identify how justice courts and legal practitioners may use AI to retrieve similar cases. Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), automation techniques were used to expedite the literature review. In this study, we confirmed the feasibility of automation tools for expediting literature reviews and provided an overview of the current research state on legal precedents retrieval.
