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Developing computational models of discretion to build legal knowledge based systems

  • Yaakov Ha Cohen Kerner
  • , Uri Schild
  • , John Zeleznikow
  • Jerusalem College of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Few legal knowledge based systems have been constructed which provide numerical advice. None have been built in discretionary domains. Our research, directed towards the domains of sentencing and family law property division has lead to the development of three distinct forms of judicial discretion. To model these different discretionary domains we use diverse artificial intelligence tools including case-based reasoning and knowledge discovery from databases. We carry out a detailed comparison of two discretionary legal knowledge based systems. Judge's Apprentice is a case-based reasoner which recommends ranges of sentences for convicted Israeli rapists and robbers. SplitUp uses Knowledge Discovery from Databases to learn what percentage of marital property the partners to a divorce in Australia will receive. The systems are compared with regard to reasoning, explanation, evaluation and coping with conflicting cases.

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Artificial Intelligence and Law, ICAIL 1999
PublisherACM
Pages206-213
Number of pages8
ISBN (Print)1581131658
DOIs
StatePublished - 14 Jun 1999
Externally publishedYes
Event7th International Conference on Artificial Intelligence and Law, ICAIL 1999 - Oslo, Norway
Duration: 14 Jun 199917 Jun 1999

Publication series

NameProceedings of the International Conference on Artificial Intelligence and Law

Conference

Conference7th International Conference on Artificial Intelligence and Law, ICAIL 1999
CityOslo, Norway
Period14/06/9917/06/99

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