Big Data of Complex Networks

Author:   Matthias Dehmer ,  Frank Emmert-Streib (Queen's University Belfast, UK) ,  Stefan Pickl ,  Andreas Holzinger (Medical University Graz, AUSTRIA)
Publisher:   Taylor & Francis Inc
ISBN:  

9781498723619


Pages:   332
Publication Date:   18 August 2016
Format:   Hardback
Availability:   In Print   Availability explained
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Big Data of Complex Networks


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Author:   Matthias Dehmer ,  Frank Emmert-Streib (Queen's University Belfast, UK) ,  Stefan Pickl ,  Andreas Holzinger (Medical University Graz, AUSTRIA)
Publisher:   Taylor & Francis Inc
Imprint:   Chapman & Hall/CRC
Dimensions:   Width: 17.80cm , Height: 2.30cm , Length: 25.40cm
Weight:   0.770kg
ISBN:  

9781498723619


ISBN 10:   1498723616
Pages:   332
Publication Date:   18 August 2016
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Big Data of Complex Networks: Challenges and Perspectives. Theory and Practice of Sampling Large Networks. Scale Graph: Large-Scale Graph Analytics Library. Techniques for the Management and Querying of Big Data in Large Scale Communication Networks. Fast Heuristics for Some Covering and Dominating Problems in Large-Scale Graphs. Aspects of Large Network in Economy. Network Visualization in the Context of Large Network Analysis.

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Author Information

Matthias Dehmer studied mathematics at the University of Siegen (Germany) and received his PhD in computer science from the Technical University of Darmstadt (Germany). Afterwards, he was a research fellow at Vienna BioCenter (Austria), Vienna University of Technology, and University of Coimbra (Coimbra). He obtained his habilitation in applied discrete mathematics from the Vienna University of Technology. Currently, he is Professor at UMIT – The Health and Life Sciences University (Austria) and also holds a position at the Universit¨at der Bundeswehr M¨unchen. His research interests are in applied mathematics, bioinformatics, systems biology, graph theory, complexity, and information theory. He has written over 175 publications in his research areas. Frank Emmert-Streib studied physics at the University of Siegen, Germany, gaining his PhD in theoretical physics from the University of Bremen. He was a postdoctoral research associate at the Stowers Institute for Medical Research, Kansas City, USA, and a senior fellow at the University of Washington, Seattle, USA. Currently, he is a lecturer/assistant professor at the Queen’s University Belfast, UK, at the Center for Cancer Research and Cell Biology, heading the Computational Biology and Machine Learning Lab. His research interests are in the field of computational biology, machine learning, and biostatistics in the development and application of methods from statistics and machine learning for the analysis of high-throughput data from genomics and genetics experiments.

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