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Analysis of Legal Argumentation Documents = A Computational Argumentation Approach /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Analysis of Legal Argumentation Documents/ by Hayato Hirata, Katsumi Nitta.
Reminder of title:
A Computational Argumentation Approach /
Author:
Hirata, Hayato.
other author:
Nitta, Katsumi.
Description:
XIII, 155 p. 1 illus.online resource. :
Contained By:
Springer Nature eBook
Subject:
Social legislation. -
Online resource:
https://doi.org/10.1007/978-981-19-2928-1
ISBN:
9789811929281
Analysis of Legal Argumentation Documents = A Computational Argumentation Approach /
Hirata, Hayato.
Analysis of Legal Argumentation Documents
A Computational Argumentation Approach /[electronic resource] :by Hayato Hirata, Katsumi Nitta. - 1st ed. 2022. - XIII, 155 p. 1 illus.online resource. - Translational Systems Sciences,292197-8840 ;. - Translational Systems Sciences,2.
Chapter 1. Introduction -- Chapter 2. Related Research -- Chapter 3 -- Factor-Based Argumentation Evaluation -- Chapter 4. Case Analysis Using Factors and Legal Topoi -- Chapter 5. Case Analysis for Case Law Education using Factors and Computational Argumentation Theory -- Chapter 6. Conclusion.
This book introduces methods to analyze legal documents such as negotiation records and legal precedents, using computational argumentation theory. First, a method to automatically evaluate argumentation skills from the records of argumentation exercises is proposed. In law school, argumentation exercises are often conducted and many records of them are produced. From each utterance in the record, a pattern of “speech act +factor” is extracted, and argumentation skills are evaluated from the sequences of the patterns, using a scoring prediction model constructed by multiple regression analyses between the appearance pattern and the scoring results. The usefulness of this method is shown by applying it to the example case “the garbage house problem”. Second, a method of extracting factors (elements that characterize precedents and cases) and legal topoi from individual precedents and using them as the expression of precedents to analyze how the pattern of factors and legal topoi appearing in a group of precedents affects the judgment (plaintiff wins/defendant wins) is proposed. This method has been applied to a group of tax cases. Third, the logical structure of 70 labor cases is described in detail by using factors and a bipolar argumentation framework (BAF) and an (extended argumentation framework (EAF) together. BAF describes the logical structure between plaintiff and defendant, and EAF describes the decision of the judge. Incorporating the legal topoi into the EAF of computational argumentation theory, the strength of the analysis of precedents by combined use of factored BAF and EAF, not only which argument the judge adopted could be specified. It was also possible to determine what kind of value judgment was made and to verify the logic. The analysis methods in this book demonstrate the application of logic-based AI methods to the legal domain, and they contribute to the education and training of law school students in logical ways of argumentation.
ISBN: 9789811929281
Standard No.: 10.1007/978-981-19-2928-1doiSubjects--Topical Terms:
783061
Social legislation.
LC Class. No.: K1700-1973
Dewey Class. No.: 344.01
Analysis of Legal Argumentation Documents = A Computational Argumentation Approach /
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This book introduces methods to analyze legal documents such as negotiation records and legal precedents, using computational argumentation theory. First, a method to automatically evaluate argumentation skills from the records of argumentation exercises is proposed. In law school, argumentation exercises are often conducted and many records of them are produced. From each utterance in the record, a pattern of “speech act +factor” is extracted, and argumentation skills are evaluated from the sequences of the patterns, using a scoring prediction model constructed by multiple regression analyses between the appearance pattern and the scoring results. The usefulness of this method is shown by applying it to the example case “the garbage house problem”. Second, a method of extracting factors (elements that characterize precedents and cases) and legal topoi from individual precedents and using them as the expression of precedents to analyze how the pattern of factors and legal topoi appearing in a group of precedents affects the judgment (plaintiff wins/defendant wins) is proposed. This method has been applied to a group of tax cases. Third, the logical structure of 70 labor cases is described in detail by using factors and a bipolar argumentation framework (BAF) and an (extended argumentation framework (EAF) together. BAF describes the logical structure between plaintiff and defendant, and EAF describes the decision of the judge. Incorporating the legal topoi into the EAF of computational argumentation theory, the strength of the analysis of precedents by combined use of factored BAF and EAF, not only which argument the judge adopted could be specified. It was also possible to determine what kind of value judgment was made and to verify the logic. The analysis methods in this book demonstrate the application of logic-based AI methods to the legal domain, and they contribute to the education and training of law school students in logical ways of argumentation.
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