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Pacific-Asia Conference on Knowledge Discovery and Data Mining

PAKDD 1998: Research and Development in Knowledge Discovery and Data Mining pp 336–347Cite as

Knowledge discovery in discretionary legal domains

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1394))

Abstract

Significant obstacles must be overcome if knowledge discovery techniques are to be applied in the legal domain. In this paper we argue that in order to use knowledge discovery in the legal domain it is essential to use domain expertise and important that an abundance of commonplace cases is available.

Even with appropriate data, data mining techniques in law must deal with contradictory cases and use statistical techniques in order to define error and estimate performance. We illustrate these points by describing our own error heuristic and the method we use for dealing with contradictions for the training of neural networks in the domain of property proceedings in Australian Family Law. In law, an explanation for a decision reached is often more important than the decision. We advocate the use of a theory of argumentation developed by the British philosopher Stephen Toulmin to provide explanations to support the outcomes predicted by our knowledge discovery system Split Up. We also discuss the use genetic algorithms to minimise the number of features our knowledge discovery system must use.

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Author information

Authors and Affiliations

  1. Database Research Laboratory, Applied Computing Research Institute, 3083, Bundoora, Victoria, Australia

    John Zeleznikow

  2. School of Information Technology and Mathematical Sciences, University of Ballarat, 3353, Ballarat, Victoria, Australia

    Andrew Stranieri

Authors
  1. John Zeleznikow
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  2. Andrew Stranieri
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Editor information

Editors and Affiliations

  1. School of Computer Science and Software Engineering, Monash university, 900 Dandenong Road, Caulfield East, Victoria, 3145, Australia

    Xindong Wu

  2. Department of Computer Science, The University of Melbourne, Parkville, Victoria, 3052, Australia

    Ramamohanarao Kotagiri

  3. School of Computer Science and Engineering, Monash university, Clayton, Victoria, 3168, Australia

    Kevin B. Korb

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© 1998 Springer-Verlag Berlin Heidelberg

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Zeleznikow, J., Stranieri, A. (1998). Knowledge discovery in discretionary legal domains. In: Wu, X., Kotagiri, R., Korb, K.B. (eds) Research and Development in Knowledge Discovery and Data Mining. PAKDD 1998. Lecture Notes in Computer Science, vol 1394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64383-4_28

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  • DOI: https://doi.org/10.1007/3-540-64383-4_28

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64383-8

  • Online ISBN: 978-3-540-69768-8

  • eBook Packages: Springer Book Archive

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