A Large Case-Based Reasoner for Legal Cases

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.