Knowledge Discovery from Legal Databases
By: Stranieri, Andrew [author.].
Contributor(s): Zeleznikow, John [author.] | SpringerLink (Online service).
Material type:
BookSeries: Law and Philosophy Library: 69Publisher: Dordrecht : Springer Netherlands : Imprint: Springer, 2005.Description: XII, 298 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781402030376.Subject(s): Computer science | Artificial intelligence | Law -- Philosophy | Law | Computer Science | Artificial Intelligence (incl. Robotics) | Theories of Law, Philosophy of Law, Legal HistoryDDC classification: 006.3 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
E books
|
PK Kelkar Library, IIT Kanpur | Available | EBK1718 |
Legal Issues in the Data Selection Phase -- Legal Issues in the Data Pre-Processing Phase -- Legal Issues in the Data Transformation Phase -- Data Mining with Rule Induction -- Uncertain and Statistical Data Mining -- Data Mining Using Neural Networks -- Information Retrieval and Text Mining -- Evaluation, Deployment and Related Issues -- Conclusion.
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.
There are no comments for this item.