Knowledge Discovery from Legal Databases
Type de ressource
Auteurs/contributeurs
- Stranieri, Andrew (Auteur)
- Zeleznikow, John (Auteur)
Titre
Knowledge Discovery from Legal Databases
Résumé
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.
Maison d’édition
Springer Science & Business Media
Date
2007
Nb de pages
307
Langue
en
ISBN
978-1-4020-3037-6
Catalogue de bibl.
Google Books
Référence
Stranieri, A. et Zeleznikow, J. (2007). Knowledge Discovery from Legal Databases. Springer Science & Business Media. https://books.google.ca/books?hl=fr&lr=&id=_niZQz0hxnUC&oi=fnd&pg=PR7&dq=description+%22legal+databases%22&ots=yBBJhrCwv9&sig=Myqg_5LcyKKPqlf10SsZGGIUYKs&redir_esc=y#v=onepage&q=description%20%22legal%20databases%22&f=false
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