Relational Data Mining

Name: Relational Data Mining
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 9783642076046
Price: 553.98 RON
Availability: InStock

Autor: Saso Dzeroski, Nada Lavrac

Limbă:

Legare: Carte broșată

Editura: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Disponibilitate: În depozitul extern

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553.98 lei

As the first book devoted to relational data mining, this coherently written multi-author monograph...

Informații despre carte

Autor

Saso Dzeroski, Nada Lavrac

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2010

Pagini

398

EAN

9783642076046

ISBN

3642076041

Enbook ID

01652721

Editura

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Greutate

633

Dimensiuni

156 x 235 x 23

Descriere completă

As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining.This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area.The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining.This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.

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