Open AccessApplication of Machine Learning for E-justice
Author(s) -
Oleg G. Metsker,
Егор Викторович Трофимов,
Georgy Kopanitsa
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1828/1/012006
Subject(s) - computer science , interpretability , scalability , artificial intelligence , machine learning , structuring , decision support system , service (business) , law enforcement , knowledge management , software engineering , database , law , economy , political science , economics
Decision support systems (DSS) in law enforcement have a long history. Starting from the late 50s, they have been developed through several architectural approaches. Still, having a proven capability of DSSes to improve legal practice, the real-world application is limited due to multiple issues, including lack of trust, interpretability, validity, scalability, etc. The paper develops a service-based decision support platform for machine learning applications for eGovernance and internal policy modelling and presents a case study of the application of the platform for the case of migration law enforcement. We have developed a decision support platform a number of micro services that connect with each other asynchronously via the REST protocol. The artificial intelligence core of the platform was built upon a knowledge base, which includes machine learning models and methods. In this work we have developed a method of structuring, analysis of legal data models based on machine learning. In the course of computational experiment, the efficiency of the developed method was proved and the interpretation of the obtained results was performed to provide recommendations for the enhancement of administrative regulation.