Computational network science : an algorithmic approach / Henry Hexmoor.
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Item type | Current library | Call number | Copy number | Status | Notes | Date due | Barcode |
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Female Library | TK5105.59 .H47 2015 (Browse shelf (Opens below)) | 1 | Available | STACKS | 51952000202264 | |
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Main Library | TK5105.59 .H47 2015 (Browse shelf (Opens below)) | 1 | Available | STACKS | 51952000202271 |
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TK5105.59 .F86 2005 Network security technologies / | TK5105.59 .H32 2006 Hacking exposed Cisco networks : Cisco security secrets & solutions / | TK5105.59 .H357 2005 Network security : a practical approach / | TK5105.59 .H47 2015 Computational network science : an algorithmic approach / | TK5105.59 .H66 2006 Enterprise Web services security / | TK5105.59 .J65 2006 Anti-hacker tool kit / | TK5105.59 .L32 2005 Network security fundamentals / |
"Networking communications." -- cover.
Includes bibliographical references.
1. Ubiquity of networks -- 2. Network analysis -- 3. Network games -- 4. Balance theory -- 5. Network dynamics -- 6. Diffusion and contagion -- 7. Influence diffusion and contagion -- 8. Power in exchange networks -- 9. Economic networks -- 10. Network capital -- 11. Network organizations -- 12. Emerging trends.
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. Network researchers and graduate students; professionals in computational disciplines; researchers in most scientific, social, and cross-disciplinary fields.
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