Text and Data Mining Techniques in Judgment Open Data Analysis for Administrative Practice Control

  • Oleg MetskerEmail author
  • Egor Trofimov
  • Sergey Sikorsky
  • Sergey Kovalchuk
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 947)


This paper represents the study results of machine learning methods application for the analysis of judgment open data. The study is dedicated to develop empirical ways to identify the relationships and the structure of administrative law enforcement process based on semi-structured data analysis and give recommendations for improving the administrative regulation. The results of the research can be us ed for legislative, analytical and law enforcement activities in the field of governmental regulation. In the course of data analysis, the models based on decision trees and other machine learning methods is developed. In addition, the models for extracting information from semi-structured texts of court decisions is developed. Moreover, a predictive model of appeal outcome is developed. The effectiveness of the established methods are demonstrated in the recommendation cases for improving the current legislation by the example of administrative law for reducing the burden on public administration.


e-government Data mining Text mining Machine learning Law Modeling Legaltech Govtech 



This research is financially supported by The Russian Science Foundation, Agreement #14-11-00823.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Oleg Metsker
    • 1
    Email author
  • Egor Trofimov
    • 2
  • Sergey Sikorsky
    • 1
  • Sergey Kovalchuk
    • 1
  1. 1.ITMO UniversitySaint PetersburgRussia
  2. 2.All-Russian State University of JusticeMoscowRussia

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