Analysing the Impact of Legal Change through Case Classification

Autor: Slingerland, R., Boer, A., Winkels, R., Palmirani, M.
Přispěvatelé: FdR overig onderzoek, Leibniz (FdR), ACIL (FdR), Bonger (FdR), PPLE (FdR)
Jazyk: angličtina
Rok vydání: 2018
Zdroj: Legal Knowledge and Information Systems: JURIX 2018: The Thirty-first Annual Conference, 121-130
STARTPAGE=121;ENDPAGE=130;TITLE=Legal Knowledge and Information Systems
Popis: In this paper an automated solution for finding cases for analysing the impact of legal change is proposed and the results are analysed with the help of a legal expert. It focuses on the automatic classification of 15,000 judgments within civil law. We investigated to what extent several machine learning algorithms were able to classify cases 'correctly'. This was done with accuracies around 0.85. However, the data were scarce and the initial labelling not perfect, so further research should focus on these aspects to improve the analysis of the impact of legal change.
Databáze: OpenAIRE