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Books > Computing & IT > Computer programming
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Big Data of Complex Networks (Paperback)
Loot Price: R1,423
Discovery Miles 14 230
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Big Data of Complex Networks (Paperback)
Series: Chapman & Hall/CRC Big Data Series
Expected to ship within 12 - 17 working days
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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. Key features: Provides a complete discussion of
both the hardware and software used to organize big data Describes
a wide range of useful applications for managing big data and
resultant data sets Maintains a firm focus on massive data and
large networks Unveils innovative techniques to help readers handle
big data Matthias Dehmer received his PhD in computer science from
the Darmstadt University of Technology, Germany. Currently, he is
Professor at UMIT - The Health and Life Sciences University,
Austria, and the Universitat der Bundeswehr Munchen. His research
interests are in graph theory, data science, complex networks,
complexity, statistics and information theory. Frank Emmert-Streib
received his PhD in theoretical physics from the University of
Bremen, and is currently Associate professor at Tampere University
of Technology, Finland. His research interests are in the field of
computational biology, machine learning and network medicine.
Stefan Pickl holds a PhD in mathematics from the Darmstadt
University of Technology, and is currently a Professor at
Bundeswehr Universitat Munchen. His research interests are in
operations research, systems biology, graph theory and discrete
optimization. Andreas Holzinger received his PhD in cognitive
science from Graz University and his habilitation (second PhD) in
computer science from Graz University of Technology. He is head of
the Holzinger Group HCI-KDD at the Medical University Graz and
Visiting Professor for Machine Learning in Health Informatics
Vienna University of Technology.
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