Data Mining and Knowledge Discovery for Big Data: Methodologies, Challenge and Opportunities - Couverture souple

9783662509456: Data Mining and Knowledge Discovery for Big Data: Methodologies, Challenge and Opportunities

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ISBN 10 : 3662509458 ISBN 13 : 9783662509456

Editeur : Springer, 2016

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The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease. Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation.

The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.

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�diteurSpringer
Date d'�dition2016
ISBN 10 3662509458
ISBN 13 9783662509456
ReliureBroch�
Langueanglais
Nombre de pages324
�diteurChu Wesley W.
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Data Mining and Knowledge Discovery for Big Data

Chu, Wesley W.

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Data Mining and Knowledge Discovery for Big Data : Methodologies, Challenge and Opportunities

Wesley W. Chu

Edit� par Springer Berlin Heidelberg, 2016

ISBN 10 : 3662509458 ISBN 13 : 9783662509456

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease. Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization. N� de r�f. du vendeur 9783662509456

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Data Mining and Knowledge Discovery for Big Data

Wesley W. Chu

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ISBN 10 : 3662509458 ISBN 13 : 9783662509456

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease. Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization. 324 pp. Englisch. N� de r�f. du vendeur 9783662509456

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Data Mining and Knowledge Discovery for Big Data

Wesley W. Chu

Edit� par Springer Berlin Heidelberg, Springer Berlin Heidelberg Aug 2016, 2016

ISBN 10 : 3662509458 ISBN 13 : 9783662509456

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Taschenbuch. Etat : Neu. Neuware -The field of data mining has made significant and far-reaching advances over the past three decades.Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease. Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation.The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 324 pp. Englisch. N� de r�f. du vendeur 9783662509456

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