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Abstracting of legal cases: The potential of clustering based on the selection of representative objects

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  • Marie‐Francine Moens
  • Caroline Uyttendaele
  • Jos Dumortier

Abstract

The SALOMON project automatically summarizes Belgian criminal cases in order to improve access to the large number of existing and future court decisions. SALOMON extracts text units from the case text to form a case summary. Such a case summary facilitates the rapid determination of the relevance of the case or may be employed in text search. An important part of the research concerns the development of techniques for automatic recognition of representative text paragraphs (or sentences) in texts of unrestricted domains. These techniques are employed to eliminate redundant material in the case texts, and to identify informative text paragraphs which are relevant to include in the case summary. An evaluation of a test set of 700 criminal cases demonstrates that the algorithms have an application potential for automatic indexing, abstracting, and text linking.

Suggested Citation

  • Marie‐Francine Moens & Caroline Uyttendaele & Jos Dumortier, 1999. "Abstracting of legal cases: The potential of clustering based on the selection of representative objects," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 50(2), pages 151-161.
    • Handle: RePEc:bla:jamest:v:50:y:1999:i:2:p:151-161
    DOI: 10.1002/(SICI)1097-4571(1999)50:23.0.CO;2-I
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    File URL: https://doi.org/10.1002/(SICI)1097-4571(1999)50:23.0.CO;2-I
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    Cited by:

    1. So-Hui Park & Dong-Gu Lee & Jin-Sung Park & Jun-Woo Kim, 2021. "A Survey of Research on Data Analytics-Based Legal Tech," Sustainability, MDPI, vol. 13(14), pages 1-24, July.

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