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Chapter

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Title

On Integrating and Classifying Legal Text Documents

Authors

[ 1 ] Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ 2 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2020

Chapter type

chapter in monograph / paper

Publication language

english

Keywords
EN
  • legal text document integration
  • text analytics
  • text document classification
Abstract

EN This paper presents an exhaustive and unified dataset based on the European Court of Human Rights judgments since its creation. The interest of such database is explained through the prism of the researcher, the data scientist, the citizen and the legal practitioner. Contrarily to many datasets, the creation process, from the collection of raw data to the feature transformation, is provided under the form of a collection of fully automated and open-source scripts. It ensures reproducibility and a high level of confidence in the processed data, which is some of the most important issues in data governance nowadays. A first experimental campaign is performed to study some predictability properties and to establish baseline results on popular machine learning algorithms. The results are consistently good across the binary datasets with an accuracy comprised between 75.86% and 98.32% for a micro-average accuracy of 96.44%.

Pages (from - to)

385 - 399

DOI

10.1007/978-3-030-59003-1_25

URL

https://link.springer.com/chapter/10.1007/978-3-030-59003-1_25

Book

Database and Expert Systems Applications : 31st International Conference, DEXA 2020, Bratislava, Slovakia, September 14–17, 2020, Proceedings, Part I

Presented on

31st International Conference on Database and Expert Systems Applications, DEXA 2020, 4-17.09.2020, Bratislava, Slovac Republic

Ministry points / chapter

20

Ministry points / conference (CORE)

70

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