Scientific paper resulting from the work of Adriana Jacoto Unger. Published at the 18th International Conference on Artificial Intelligence and Law and presented by Adriana in an online session. The paper features collaboration from researchers José Francisco dos Santos Neto, Prof. Dr. Marcelo Fantinato (Adriana’s advisor), Prof. Dr. Sarajane Marques Peres, Julio Trecenti e Renata Hirota.
Abstract: Improving judicial performance has become increasingly relevant to guarantee access to justice for all, worldwide. In this context, technology-enabled tools to support lawsuit processing emerge as powerful allies to enhance the justice efficiency. Using electronic lawsuit management systems within the courts of justice is a widespread practice, which also leverages production of big data within judicial operation. Some jurimetrics techniques have arisen to evaluate efficiency based on statistical analysis and data mining of data produced by judicial information systems. In this sense, the process mining area offers an innovative approach to analyze judicial data from a process-oriented perspective. This paper presents the application of process mining in a event log derived from a dataset containing business lawsuits from the Court of Justice of the State of Sao Paulo, Brazil – the largest court in the world – in order to analyze judicial performance. Although the results show these lawsuits have an ad hoc sequence flow, process mining analysis have allowed to identify most frequent activities and process bottlenecks, providing insights into the root causes of inefficiencies.
Complete paper here (ACM Digital Library).
Reference: Adriana Jacoto Unger, José Francisco dos Santos Neto, Marcelo Fantinato, Sarajane Marques Peres, Julio Trecenti, and Renata Hirota. 2021. Process mining-enabled jurimetrics: analysis of a Brazilian court’s judicial performance in the business law processing. In Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law (ICAIL ’21). Association for Computing Machinery, New York, NY, USA, 240–244. https://doi.org/10.1145/3462757.3466137
@inproceedings{Unger2021,
author = {Unger, Adriana Jacoto and Neto, Jos\'{e} Francisco dos Santos and Fantinato, Marcelo and Peres, Sarajane Marques and Trecenti, Julio and Hirota, Renata},
title = {Process Mining-Enabled Jurimetrics: Analysis of a Brazilian Court’s Judicial Performance in the Business Law Processing},
year = {2021},
isbn = {9781450385268},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3462757.3466137},
doi = {10.1145/3462757.3466137},
booktitle = {Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law},
pages = {240–244},
numpages = {5},
keywords = {business law, process mining, business process management, jurimetrics, judicial performance, administration of justice, procedural law, legal informatics},
location = {S~{a}o Paulo, Brazil},
series = {ICAIL ’21}}
Artigo científico resultante do trabalho de Adriana Jacoto Unger. Publicado no 18th International Conference on Artificial Intelligence and Law e apresentado por Adriana em sessão online. O artigo foi escrito pro Adriana em colaboração com José Francisco dos Santos Neto, Prof. Dr. Marcelo Fantinato (orientador de Adriana), Prof. Dr. Sarajane Marques Peres, Julio Trecenti e Renata Hirota.
Artigo completo aqui – em ingles (ACM Digital Library).
Referência: Adriana Jacoto Unger, José Francisco dos Santos Neto, Marcelo Fantinato, Sarajane Marques Peres, Julio Trecenti, and Renata Hirota. 2021. Process mining-enabled jurimetrics: analysis of a Brazilian court’s judicial performance in the business law processing. In Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law (ICAIL ’21). Association for Computing Machinery, New York, NY, USA, 240–244. https://doi.org/10.1145/3462757.3466137
@inproceedings{Unger2021,
author = {Unger, Adriana Jacoto and Neto, Jos\'{e} Francisco dos Santos and Fantinato, Marcelo and Peres, Sarajane Marques and Trecenti, Julio and Hirota, Renata},
title = {Process Mining-Enabled Jurimetrics: Analysis of a Brazilian Court’s Judicial Performance in the Business Law Processing},
year = {2021},
isbn = {9781450385268},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3462757.3466137},
doi = {10.1145/3462757.3466137},
booktitle = {Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law},
pages = {240–244},
numpages = {5},
keywords = {business law, process mining, business process management, jurimetrics, judicial performance, administration of justice, procedural law, legal informatics},
location = {S~{a}o Paulo, Brazil},
series = {ICAIL ’21}
}
