Abstract
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%.
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Quemy, A., Wrembel, R. (2020). On Integrating and Classifying Legal Text Documents. In: Hartmann, S., Küng, J., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2020. Lecture Notes in Computer Science(), vol 12391. Springer, Cham. https://doi.org/10.1007/978-3-030-59003-1_25
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