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Machine Learning versus Knowledge Based Classification of Legal Texts
Emile de Maat, Kai Krabben, Radboud Winkels
87 - 96
10.3233/978-1-60750-682-9-87
Frontiers in Artificial Intelligence and Applications
Volume 223: Legal Knowledge and Information Systems
Abstract

This paper presents results of an experiment in which we used machine learning (ML) techniques to classify sentences in Dutch legislation. These results are compared to the results of a pattern-based classifier. Overall, the ML classifier performs as accurate (>90%) as the pattern based one, but seems to generalize worse to new laws. Given these results, the pattern based approach is to be preferred since its reasons for classification are clear and can be used for further modelling of the content of the sentences.

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