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UBC Theses and Dissertations
Neural networks for legal quantum prediction Terrett, Andrew J.
Abstract
This thesis argues that Artificial Neural Networks (ANN's) have applications within the domain of law and can be built using readily available Artificial Intelligence software for the Personal Computer. In order to demonstrate this, I have built working ANN's using data made available to me by the Faculty of Law Artificial Intelligence Research Project (FLAIR) and Windows™-based ANN software that is commercially available. The reasons for building a system are three-fold. First, a working system is the most graphic demonstration of my above assertion. Secondly, given my background as a practitioner in law, I am concerned to ensure the quick, efficient movement of law-related technology from research laboratory to marketplace. Thirdly, the building of a neural network avails me with the opportunity to analyze comparatively the performance of the ANN's with statistical and expert system models which used the same data and were also built at the FLAIR project. The theoretical foundation for this thesis is the view that, although many legal decisions are often reducible to a set of doctrines, policies or sub-doctrinal rules, certain domains of legal decision-making evade analysis using a rule-based paradigm. Thus, although relational patterns between any given facts and the law exist, they cannot always be described. Therefore in order to build "intelligent" computer programs that can assist the lawyer in his or her work, we should explore the potential of and utilize those tools that can find relational patterns automatically. Having done this, we should attempt to combine the same with those software tools that we understand more fully, namely expert systems and traditional programming methods. The use of hybrid neural network/expert system programs is well developed in many other domains. Legal researchers, however, have yet to even thoroughly examine neural networks as an isolated technology. This thesis is an attempt to right this imbalance.
Item Metadata
Title |
Neural networks for legal quantum prediction
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
1994
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Description |
This thesis argues that Artificial Neural Networks (ANN's) have applications within the
domain of law and can be built using readily available Artificial Intelligence software for
the Personal Computer. In order to demonstrate this, I have built working ANN's using
data made available to me by the Faculty of Law Artificial Intelligence Research Project
(FLAIR) and Windows™-based ANN software that is commercially available. The
reasons for building a system are three-fold. First, a working system is the most graphic
demonstration of my above assertion. Secondly, given my background as a practitioner in
law, I am concerned to ensure the quick, efficient movement of law-related technology
from research laboratory to marketplace. Thirdly, the building of a neural network avails
me with the opportunity to analyze comparatively the performance of the ANN's with
statistical and expert system models which used the same data and were also built at the
FLAIR project.
The theoretical foundation for this thesis is the view that, although many legal decisions
are often reducible to a set of doctrines, policies or sub-doctrinal rules, certain domains of
legal decision-making evade analysis using a rule-based paradigm. Thus, although
relational patterns between any given facts and the law exist, they cannot always be
described. Therefore in order to build "intelligent" computer programs that can assist the
lawyer in his or her work, we should explore the potential of and utilize those tools that
can find relational patterns automatically. Having done this, we should attempt to
combine the same with those software tools that we understand more fully, namely expert
systems and traditional programming methods. The use of hybrid neural network/expert
system programs is well developed in many other domains. Legal researchers, however,
have yet to even thoroughly examine neural networks as an isolated technology. This
thesis is an attempt to right this imbalance.
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Extent |
9492124 bytes
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Genre | |
Type | |
File Format |
application/pdf
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Language |
eng
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Date Available |
2009-01-09
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Provider |
Vancouver : University of British Columbia Library
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Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
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DOI |
10.14288/1.0077428
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
1995-05
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Campus | |
Scholarly Level |
Graduate
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Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.