Abstract
Within the last decade text mining, i.e., extracting sensitive information from text corpora, has become a major factor in business intelligence. The automated textual analysis of law corpora is highly valuable because of its impact on a company’s legal options and the raw amount of available jurisdiction. The study of supreme court jurisdiction and international law corpora is equally important due to its effects on business sectors.
In this paper we use text mining methods to investigate Austrian supreme administrative court jurisdictions concerning dues and taxes. We analyze the law corpora using R with the new text mining package tm. Applications include clustering the jurisdiction documents into groups modeling tax classes (like income or value-added tax) and identifying jurisdiction properties. The findings are compared to results obtained by law experts.
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Feinerer, I., Hornik, K. (2008). Text Mining of Supreme Administrative Court Jurisdictions. In: Preisach, C., Burkhardt, H., Schmidt-Thieme, L., Decker, R. (eds) Data Analysis, Machine Learning and Applications. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78246-9_67
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DOI: https://doi.org/10.1007/978-3-540-78246-9_67
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