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.
| ISBN: | 9781402030369 |
| Publication date: | 1st June 2005 |
| Author: | Andrew Stranieri, J Zeleznikow |
| Publisher: | Springer an imprint of Springer Netherlands |
| Format: | Hardback |
| Pagination: | 294 pages |
| Series: | Law and Philosophy Library |
| Genres: |
Artificial intelligence Methods, theory and philosophy of law |
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.
Knowledge Discovery from Legal Databases features in the following genres: Artificial intelligence, Methods, theory and philosophy of law
Hardback. Not Available.
Knowledge Discovery from Legal Databases was written by Andrew Stranieri, J Zeleznikow and published by Springer an imprint of Springer Netherlands
Knowledge Discovery from Legal Databases has 294 pages
Yes it is part of Law and Philosophy Library series