Application of Case Based Reasoning in Legal Knowledge Based System: A Prototype on Children Criminal Cases in Ethiopia
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Date
2010-01
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Addis Ababa University
Abstract
The target of Artificial Intelligence is to make computer behave intelligent. This is causing the
development of many subfields; among which Case -Based Reasoning (CBR) is one of the
hottest subfield of AI. Case-Based Reasoning (CBR) proposes the reuse of past experiences
and cases to solve new problems. Law is an excellent domain for studying case-based
reasoning that enables the reuse of the information contained in the cases to solve problems
from diverse areas.
The goal of this thesis is to design prototype, case based reasoning in legal knowledge based
system that advises in the investigation of children criminal cases. This paper describes
Judicial Application, a case-based system that is able to adjust its retrieval and adaptation
metrics, in addition to storing cases. Standard case representation to the original knowledge
source (legal cases) has been used to store legal cases.
The prototype is developed using the Object-Oriented framework jCOLIBRI1.0. The CBR
model has been effectively used to retrieve analogues previous cases in reaching a potential
solution for decision making and also a means to adopt the current case of a problem for the
future use. To enhance the effectiveness of the legal argument, local similarity matching and
weight of the attributes are adopted to compare the equivalent values of a problem of a case
and source cases. The performance of the system is evaluated using statistical analysis which
results with average precision value 82.75% and user satisfaction which shows the suitability
of CBR for designing legal knowledge based system. To improve the performance of the
system the researcher mainly recommends the need for upgrading the capacity of the case
using integrated domain knowledge to have a precise and up-to-date decision processing.
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Keywords
Based Reasoning in Legal Knowledge Based System