*Price HAS BEEN REDUCED by 10% until Monday, May 12 (weekend sale item)* Second Edition, 1285 pp., hardcover, new. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. N� de ref. del art�culo ZB1317377

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Detalles bibliogr�ficos

T�tulo: Data Mining and Knowledge Discovery Handbook...

Editorial: Springer

A�o de publicaci�n: 2010

Encuadernaci�n: Encuadernaci�n de tapa dura

Condici�n: New

Edici�n: 2� Edici�n

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Sinopsis:

<P>THIS BOOK ORGANIZES KEY CONCEPTS, THEORIES, STANDARDS, METHODOLOGIES, TRENDS, CHALLENGES AND APPLICATIONS OF DATA MINING AND KNOWLEDGE DISCOVERY IN DATABASES. IT FIRST SURVEYS, THEN PROVIDES COMPREHENSIVE YET CONCISE ALGORITHMIC DESCRIPTIONS OF METHODS, INCLUDING CLASSIC METHODS PLUS THE EXTENSIONS AND NOVEL METHODS DEVELOPED RECENTLY. IT ALSO GIVES IN-DEPTH DESCRIPTIONS OF DATA MINING APPLICATIONS IN VARIOUS INTERDISCIPLINARY INDUSTRIES.</P>

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From the reviews of the second edition:

“This handbook provides an excellent guide in every aspect of the discovery process. ... Contributors are drawn from noted academic institutions and companies around the world and across diverse disciplines. ... serves to define the current state of the art in knowledge discovery, and is particularly useful in cross-fertilization among a diverse set of application scenarios. It is an indispensable reference for researchers and an excellent starting point for advanced students taking graduate courses in this area. Summing Up: Highly recommended. Upper-division undergraduates through professionals/practitioners.” (J. Y. Cheung, Choice, Vol. 48 (10), June, 2011)

“This edition treats new aspects (for instance, privacy) and new methods, like those based on swarm intelligence and multi-label classification. ... The book is a comprehensive and detailed reference. ... Each chapter contains a long list of references for further investigation. ... I recommend this comprehensive book to advanced readers--including designers and architects at software companies--interested in the R&D of data mining.” (K. Balogh, ACM Computing Reviews, November, 2011)

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