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Computational Network Science

An Algorithmic Approach

Language EnglishEnglish
E-book Adobe ePub DRM
E-book Computational Network Science Henry Hexmoor
Libristo code: 39576378
Publishers Morgan Kaufmann, September 2014
The emerging field of network science represents a new style of research that can unify such traditi... Full description
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The emerging field of network science represents a new style of research that can unify such traditionally-diverse fields as sociology, economics, physics, biology, and computer science. It is a powerful tool in analyzing both natural and man-made systems, using the relationships between players within these networks and between the networks themselves to gain insight into the nature of each field. Until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has kept it from being a truly universal discipline. Computational Network Science seeks to unify the methods used to analyze these diverse fields. This book provides an introduction to the field of Network Science and provides the groundwork for a computational, algorithm-based approach to network and system analysis in a new and important way. This new approach would remove the need for tedious human-based analysis of different datasets and help researchers spend more time on the qualitative aspects of network science research.Demystifies media hype regarding Network Science and serves as a fast-paced introduction to state-of-the-art concepts and systems related to network scienceComprehensive coverage of Network Science algorithms, methodologies, and common problemsIncludes references to formative and updated developments in the fieldCoverage spans mathematical sociology, economics, political science, and biological networks

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About the book

Full name Computational Network Science
Author Henry Hexmoor
Language English
Binding E-book - Adobe ePub DRM
Date of issue 2014
Number of pages 128
EAN 9780128011560
Libristo code 39576378
Publishers Morgan Kaufmann
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