Big Data of Complex Networks

Matthias Dehmer; Frank Emmert-Streib; Stefan Pickl; Andreas Holzinger

Big Data of Complex Networks

Matthias Dehmer (Editor), Frank Emmert-Streib (Editor), Stefan Pickl (Editor), Andreas Holzinger (Editor)

Institute of Human-Centred Computing (7060)

Research output: Book/Report › Book › peer-review

Abstract

Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks.

Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics.

Original language	English
Place of Publication	Boca Raton, London, New York
Publisher	CRC Press Taylor & Francis Group
Number of pages	320
ISBN (Print)	9781498723619
Publication status	Published - 16 Sept 2016

Keywords

Machine Learning
Graph-Based Data Mining
Knowledge Discovery
Network Science
Complex Networks

ASJC Scopus subject areas

Artificial Intelligence

Fields of Expertise

Information, Communication & Computing

Treatment code (Nähere Zuordnung)

Basic - Fundamental (Grundlagenforschung)

Access to Document

Big-Data-Complex-Networks

Cite this

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AB - Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks.Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics.

KW - Machine Learning

KW - Graph-Based Data Mining

KW - Knowledge Discovery

KW - Network Science

KW - Complex Networks

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BT - Big Data of Complex Networks

PB - CRC Press Taylor & Francis Group

CY - Boca Raton, London, New York

ER -

Big Data of Complex Networks

Abstract

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Machine Learning for Biomedical Knowledge Discovery

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Big Data of Complex Networks

Abstract

Keywords

ASJC Scopus subject areas

Fields of Expertise

Treatment code (Nähere Zuordnung)

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Fingerprint

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Machine Learning for Biomedical Knowledge Discovery

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