A Large Case-Based Reasoner for Legal Cases

Rosina Weber-Lee
Ricardo Miranda Barcia
Marcio C. da Costa
Ilson W. Rodrigues Filho
Hugo C. Hoeschl
Tania C. DAgostini Bueno
Alejandro Martins
Roberto C. Pacheco

Federal University of Santa Catarina
LIA - Production Engineering
rolee@eps.ufsc.br


Abstract. In this paper we propose a large case-based reasoner for the legal domain.
Analyzing legal texts for indexing purposes makes the implementation of large case
bases a complex task. We present a methodology to automatically convert legal texts
into legal cases guided by domain expert knowledge in a rule-based system with
Natural Language Processing (NLP) techniques. This methodology can be generalized
to be applied in different domains making Case-Based Reasoning (CBR) paradigm a
powerful technology to solve real world problems with large knowledge sources.

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