A natural language based legal expert system for consultation and tutoring---the LEX project

Author(s):  
F. Haft ◽  
R. P. Jones ◽  
Th. Wetter
1991 ◽  
Vol 6 (4) ◽  
pp. 171-175 ◽  
Author(s):  
M Roca-Bennasar ◽  
A Garcia-Mas ◽  
N Llaneras ◽  
J Blat ◽  
P Roca

SummaryWe present the construction of an expert system (ES) for the diagnosis of Obsessive-Compulsive Disorders (OCD). It concerns an artificial intelligence tool, in Lisp language compatible with any personal computer (PC) with a hard disk. The ES asks the user 50 questions in natural language, on the patient or on a clinical history. It is provided with 115 rules of reasoning. Using single or multivaluate variables, the ES reaches the diagnosis of the Obsessive-Compulsive Disorders or the recommendations of differential diagnosis with related patterns or involucred with obsessive pathology: phobic, affective, schizophrenic and Gilles de la Tourette disorders. Finally, the perspectives for the utilisation of the ES in psychopathology are disscussed, in conjunction with the 2 serious problems created, design difficulty and user acceptance.


Author(s):  
Hajime Yoshino ◽  

Since 1992, about 30 Japanese lawyers and computer scientists have been intensively engaged in a project of systematizing and computerizing legal reasoning. This project is the Study of Development of a Legal Expert System - Exploration of Legal Knowledge Structure and Implementation of Legal Reasoning or, in short, the "Legal Expert" Project. In this paper, I would like to introduce the Legal Expert project, explaining the goals, study organizations and their tasks in constructing legal expert systems in Japan.


Author(s):  
HSU LOKE SOO

This paper presents the design and implementation of a Chinese Expert System Shell which is based on a Chinese Prolog interpreter. The system is divided into three parts: the knowledge acquisition module, the knowledge application module and the inference engine. The knowledge engineer defines the syntax of the language to be used by himself and by the users when they interact with the system. The natural language interface is table driven and can be modified easily. The system also caters for the case when the domain expert finds it difficult to articulate the rules, but is able to give examples. An inductive engine is included to extract rules from examples.


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