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Statistical Recognition of References in Czech Court Decisions

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 8856)

Abstract

We address the task of detection and classification of references in Czech court decisions, mainly we focus on references to other court decisions and acts. In addition, we are interested in detection of institutions that issued documents under consideration. We handle these references like entities in the task of Named Entity Recognition. We approach the task using machine learning methods, namely HMM and Perceptron algorithm and we report F-measure over 90% averaged over all entities. The results significantly outperform the systems published previously.

Keywords

  • Hide Markov Model
  • Resource Description Framework
  • Court Decision
  • Name Entity Recognition
  • Legal Text

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Kríž, V., Hladká, B., Dědek, J., Nečaský, M. (2014). Statistical Recognition of References in Czech Court Decisions. In: Gelbukh, A., Espinoza, F.C., Galicia-Haro, S.N. (eds) Human-Inspired Computing and Its Applications. MICAI 2014. Lecture Notes in Computer Science(), vol 8856. Springer, Cham. https://doi.org/10.1007/978-3-319-13647-9_6

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  • DOI: https://doi.org/10.1007/978-3-319-13647-9_6

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13646-2

  • Online ISBN: 978-3-319-13647-9

  • eBook Packages: Computer ScienceComputer Science (R0)