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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© 1997 Springer-Verlag Berlin Heidelberg
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Weber-Lee, R. et al. (1997). A large case-based reasoner for legal cases. In: Leake, D.B., Plaza, E. (eds) Case-Based Reasoning Research and Development. ICCBR 1997. Lecture Notes in Computer Science, vol 1266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63233-6_491
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DOI: https://doi.org/10.1007/3-540-63233-6_491
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