Relational Data Mining

Nada Lavra¿

ISBN 10: 3540422897 / ISBN 13: 9783540422891

Published by Springer Berlin Heidelberg Aug 2001, 2001

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 420 pp. Englisch.

Seller Inventory # 9783540422891

Bibliographic Details

• Title: Relational Data Mining
• Publisher: Springer Berlin Heidelberg Aug 2001
• Publication Date: 2001
• Language: English
• ISBN 10: 3540422897
• ISBN 13: 9783540422891
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 28D millimeters 241 millimeters width by 160 millimeters height by 28 millimeters depth
• Weight: 793 grams

About this title

Synopsis

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.