Overview
- Latest research on data mining
- Presents foundations, social networks and applications
- Written by leading experts in the field
Part of the book series: Studies in Big Data (SBD, volume 1)
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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.
Reviews
From the reviews:
“This book collects and collates the latest developments in data mining and knowledge discovery for big data … . This book is primarily for practicing professionals and researchers. It explains state-of-the-art methodologies, techniques, and developments in many fields of data mining. The compilation of the latest developments from diverse fields into one volume gives professionals an opportunity to learn what is happening in other fields and gain insights and knowledge that can be used in their own fields.” (Alexis Leon, Computing Reviews, February, 2014)Editors and Affiliations
Bibliographic Information
Book Title: Data Mining and Knowledge Discovery for Big Data
Book Subtitle: Methodologies, Challenge and Opportunities
Editors: Wesley W. Chu
Series Title: Studies in Big Data
DOI: https://doi.org/10.1007/978-3-642-40837-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2014
Hardcover ISBN: 978-3-642-40836-6Published: 09 October 2013
Softcover ISBN: 978-3-662-50945-6Published: 27 August 2016
eBook ISBN: 978-3-642-40837-3Published: 24 September 2013
Series ISSN: 2197-6503
Series E-ISSN: 2197-6511
Edition Number: 1
Number of Pages: X, 311
Number of Illustrations: 70 b/w illustrations, 29 illustrations in colour