Data Mining and Knowledge Discovery for Big Data

Name: Data Mining and Knowledge Discovery for Big Data
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 9783642408366
Price: 105.43 EUR
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Methodologies, Challenge and Opportunities

Автор: Wesley W. Chu

Език:

Корици: С твърди корици

Издател: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

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The field of data mining has made significant and far-reaching advances over the past three decades....

Информация за книгата

Автор

Wesley W. Chu

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2013

страници

311

EAN

9783642408366

ISBN

3642408362

Enbook ID

02075364

Издател

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Теглоt

6092

Размери

155 x 235 x 22

Пълно описание

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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Пълно описание

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