Relational Data Mining: With 79 figures and 69 tables

Dzeroski, Saso - Lavrac, Nada (eds.)

ISBN 10: 3540422897 ISBN 13: 9783540422891

Verlag: Berlin - Heidelberg - New York: Springer-Verlag 2001, 2001

Sprache: Englisch

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Beschreibung

Hardback, XIX+398 pp., 8� (16 x 24.5 cm), ex-library, two corners slightly bumped, there is a paper label on the backstrip, the front free endpaper has a blackened stamp, condition: very good Book Language/s: English.

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Bibliografische Details

Titel

Relational Data Mining: With 79 figures and 69 tables

Verlag

Berlin - Heidelberg - New York: Springer-Verlag 2001

Erscheinungsjahr

2001

Sprache

Englisch

ISBN-10

3540422897

ISBN-13

9783540422891

Einband

Hardcover

Verk�uferkataloge

�ber diesen Titel

Inhaltsangabe

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.

Von der hinteren Coverseite

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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