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: 553.26 RON
Availability: InStock

Methodologies, Challenge and Opportunities

Autor: Wesley W. Chu

Limbă:

Legare: Copertă tare

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

Disponibilitate: În depozitul extern

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

Informații despre carte

Autor

Wesley W. Chu

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2013

Pagini

311

EAN

9783642408366

ISBN

3642408362

Enbook ID

02075364

Editura

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Greutate

6092

Dimensiuni

155 x 235 x 22

Descriere completă

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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