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Data Mining and Knowledge Discovery for Big Data: Methodologies, Challenge and Opportunities: 1 (Studies in Big Data) - Hardcover
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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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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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Data Mining and Knowledge Discovery for Big Data: Methodologies, Challenge and Opportunities
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Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 2013
ISBN 10: 3642408362
ISBN 13: 9783642408366
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Hardcover. Zustand: Très bon. Ancien livre de bibliothèque. Edition 2013. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2013. Ammareal gives back up to 15% of this item's net price to charity organizations. Artikel-Nr. D-601-202
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Data Mining and knowledge discovery for big data. Methodologies, challenge and opportunities.
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X, 303 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stamped. Studies in Big Data, Vol. 1. Sprache: Englisch. Artikel-Nr. 1566CB
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Data Mining and Knowledge Discovery for Big Data: Methodologies, Challenge and Opportunities (Studies in Big Data) (Volume 1)
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Zustand: Fair. Volume 1. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9783642408366. Artikel-Nr. 7063185
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Data Mining and Knowledge Discovery for Big Data : Methodologies, Challenge and Opportunities
Verlag:
Springer Berlin Heidelberg, 2013
ISBN 10: 3642408362
ISBN 13: 9783642408366
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 316 | Sprache: Englisch | Produktart: Bücher. Artikel-Nr. 24152826/12
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Data Mining and Knowledge Discovery for Big Data: Methodologies, Challenge and Opportunities
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Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.25. Artikel-Nr. G3642408362I4N00
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Data Mining and Knowledge Discovery for Big Data
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Data Mining And Knowledge Discovery For Big Data: Methodologies, Challenge And Opportunities (Studies In Big Data)
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Data Mining and Knowledge Discovery for Big Data
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Data Mining and Knowledge Discovery for Big Data
ISBN 10: 3642408362
ISBN 13: 9783642408366
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Buch. Zustand: 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 316 pp. Englisch. Artikel-Nr. 9783642408366
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Data Mining and Knowledge Discovery for Big Data : Methodologies, Challenge and Opportunities
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Buch. Zustand: 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. Artikel-Nr. 9783642408366
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