Taking advantage of models for legal classification

ABSTRACT

Legal reasoning is often couched in terms of legal classification. We examine how three models of classification — Classical, Probabilistic and Exemplar — are used to perform legal classification. We argue that all three models of classification are implicitly applied by existing AI methods. The CABARET (“CAse-BAsed REasoning Tool”) system is suggested as an architecture that applies all three models. The relative difficulty of revising knowledge in rule form, in HYPO-style dimension form, and exemplar form is considered.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.1 Applications and Expert Systems
          Subjects: Law

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.3 Deduction and Theorem Proving
          Subjects: Answer/reason extraction
      I.2.6 Learning
          Subjects: Concept learning

General Terms:
Design, Legal Aspects