Sprache: Englisch
Verlag: Cambridge University Press, 2016
ISBN 10: 1107079497 ISBN 13: 9781107079496
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 107,31
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In den WarenkorbZustand: New. In.
EUR 155,71
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 188 pages. 9.50x6.50x0.50 inches. In Stock.
Sprache: Englisch
Verlag: Cambridge University Press, 2016
ISBN 10: 1107079497 ISBN 13: 9781107079496
Anbieter: Kennys Bookstore, Olney, MD, USA
EUR 201,65
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. This book unifies and consolidates methods for analyzing multilayer networks arising from the social and physical sciences and computing. Num Pages: 188 pages. BIC Classification: UDBS. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 228 x 152 x 15. Weight in Grams: 420. . 2016. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: Cambridge University Press, 2016
ISBN 10: 1107079497 ISBN 13: 9781107079496
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Multilayer networks, in particular multilayer social networks, where users belong to and interact on different networks at the same time, are an active research area in social network analysis, computer science, and physics. These networks have traditionally been studied within these separate research communities, leading to the development of several independent models and methods to deal with the same set of problems. This book unifies and consolidates existing practical and theoretical knowledge on multilayer networks including data collection and analysis, modeling, and mining of multilayer social network systems, the evolution of interconnected social networks, and dynamic processes such as information spreading. A single real dataset is used to illustrate the concepts presented throughout the book, demonstrating both the practical utility and the potential shortcomings of the various methods. Researchers from all areas of network analysis will learn new aspects and future directions of this emerging field.