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1 - Warat, Luis Alberto. O Direito e sua linguagem.
2ª Versão. 2ª Ed. Sergio Antonio Fabris Editor.
Porto Alegre-1995.
2 - Warat, Luis Alberto. Introdução Geral ao Direito.
III O Direito Não estudado Pela Teoria Jurídica Moderna.
Sergio Antonio Fabris Editor. Porto Alegre-1997.
3 - Book Review. Valente Andre: Legal Knwoledge Engineering; A
Modelling Approach in Frontiers in Artificial Intelligence and Applications,
Vol. 30, IOS Press, Amsterdam, the Netherlands, ISBN: 90.5199.230.0.
Artificial Intelligence and Law. Vol 7, Nº 4: 367-375, 1999.
PARA ADQUIR: http://www.kluweronline.com/issn/0924-8463
4 - Leake, David B., Plaza, Enric. Case-Based Reasoning Research
and Development. Lectures Notes in Artificial Intelligence and Law.
Second International Conference on Case-Based Reasoning, ICCBR-97.Providence,
RI USA, July 1997. Proceedings.
5 - Xu, Mingqiang; Hirrota, Kaoru and Yoshino. A fuzzy Theoretical
approach to case-based representattion and infrence in CISG. Artificial
Intelligence and Law. Vol 7, Nº 2-3: 259-272, 1999. PARA ADQUIR:
http://www.kluweronline.com/issn/0924-8463
6 - Uso da Teoria Jurídica para Recuperação
em Amplas Bases de Textos Jurídicos. T. C. D. Bueno., C.
von Wangenheim, H. Hoeschl, E. Mattos, R. M. Barcia. Anais do ENIA,
1999. v.4.p.107-120.
7 - Bueno, Tânia C. D. Representação da Informação
Jurídica em sistema baseado em casos. Direito, Sociedade
e Informática: Limites e perspectivas da vida digital. Aires
José Rover, organizador – Florianópolis: Fundação
Boiteux, 2000. 223-228.
8 - Automatic text representation, classification and labeling
in European law
Authors
Erich Schweighofer
Andreas Rauber
Michael Dittenbach
The huge text archives and retrieval systems of legal information
have not achieved yet the representation in the well-known subject-oriented
structure of legal commentaries. Content-based classification and
text analysis remains a high priority research topic. In the joint
KONTERM, SOM and LabelSOM projects, learning techniques of neural
networks are used to achieve similar high compression rates of classification
and analysis like in manual legal indexing. The produced maps of
legal text corpora cluster related documents in units that are described
with automatically selected descriptors. Extensive tests with text
corpora in European case law have shown the feasibility of this
approach. Classification and labeling proved very helpful for legal
research. The Growing Hierarchical Self-Organizing Map represents
very interesting generalities and specialties of legal text corpa.
The segmentation into document parts improved very much the quality
of labeling. The next challenge would be a change from tf x idf
vector representation to a modified vector representation taking
into account thesauri or ontologies considering learned properties
of legal test corpora.
9 - POWER: using UML/OCL for modeling legislation - an application
report
Authors
Tom M. van Engers
Rik Gerrits
Margherita Boekenoogen
Erwin Glassée
Patries Kordelaar
The Dutch Tax and Customs Administration (DTCA in Dutch: Belastingdienst)
conducts a research program POWER in which methods and tools are
developed that support a systematic translation of (new) legislation
into the DTCA's processes. The methods and tools developed help
to improve the quality of (new) legislation and codify the knowledge
used in the translation processes in which legislation and regulations
are transformed into procedures, computer programs and other designs.
Thereby the time-to-market of the implementation of legislation
will be reduced. In this article we focus on the method we developed
for modeling legislation. We will elaborate upon the principles
behind the method and explain the use of Catalysis and UML/OCL in
the modeling process. The coupling of models of legislation and
task models originating from business policy is demonstrated and
finally we will show the way knowledge-based components in function
of application are generated automatically.
10 - JurisConsulto: retrieval in jurisprudencial text bases using
juridical terminology
Authors
Tânia C. D'Agostini Bueno
Christiane Gresse von Wangenheim
Eduardo da Silva Mattos
Hugo Cesar Hoeschl
Ricardo M. Barcia
In the legal domain, jurisprudence has an important role as a juridical
source; its decisions support the application of the Law to a concrete
case. The problem is that Brazilian Courts produce an enormous amount
of decisions every year, turning these text sources larger every
time and forcing juridical professionals to spend more time in the
search for a relevant decision. Sophisticated AI techniques are
needed to minimize searches time and improves the quality and appropriateness
of the retrieved information. This paper describes a case-based
approach for the intelligent retrieval of jurisprudencial texts.
The approach enables the retrieval of adequate texts with characteristics
similar to information supplied by the user in natural language.
New documents are automatically included into the knowledge base
by extracting relevant information. In order to enable the processing
of informal textual knowledge in natural language, a controlled
vocabulary and a juridical thesaurus based on common juridical terminology,
is integrated into the retrieval and extraction process. The approach
is based on sentences to criminal proceedings in the domain of the
Brazilian Right.
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