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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Knowledge Discovery from Legal Databases is the first text to describe data mining techniques as they apply to law. Law students, legal academics and applied information technology specialists are guided thorough all phases of the knowledge discovery from databases process with clear explanations of numerous data mining algorithms including rule induction, neural networks and association rules. Throughout the text, assumptions that make data mining in law quite different to mining other data are made explicit. Issues such as the selection of commonplace cases, the use of discretion as a form of open texture, transformation using argumentation concepts and evaluation and deployment approaches are discussed at length.
Authors and Affiliations
Bibliographic Information
Book Title: Knowledge Discovery from Legal Databases
Authors: Andrew Stranieri, John Zeleznikow
Series Title: Law and Philosophy Library
DOI: https://doi.org/10.1007/1-4020-3037-1
Publisher: Springer Dordrecht
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Science+Business Media B.V. 2005
Hardcover ISBN: 978-1-4020-3036-9Published: 01 June 2005
Softcover ISBN: 978-90-481-6771-5Published: 28 October 2010
eBook ISBN: 978-1-4020-3037-6Published: 30 March 2006
Series ISSN: 1572-4395
Series E-ISSN: 2215-0315
Edition Number: 1
Number of Pages: XII, 298
Topics: Artificial Intelligence, Theories of Law, Philosophy of Law, Legal History