On Metrics And Models For Multiplex Networks


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On Metrics and Models for Multiplex Networks


On Metrics and Models for Multiplex Networks

Author:

language: en

Publisher:

Release Date: 2018


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Multiplex Networks


Multiplex Networks

Author: Emanuele Cozzo

language: en

Publisher: Springer

Release Date: 2018-06-27


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This book provides the basis of a formal language and explores its possibilities in the characterization of multiplex networks. Armed with the formalism developed, the authors define structural metrics for multiplex networks. A methodology to generalize monoplex structural metrics to multiplex networks is also presented so that the reader will be able to generalize other metrics of interest in a systematic way. Therefore, this book will serve as a guide for the theoretical development of new multiplex metrics. Furthermore, this Brief describes the spectral properties of these networks in relation to concepts from algebraic graph theory and the theory of matrix polynomials. The text is rounded off by analyzing the different structural transitions present in multiplex systems as well as by a brief overview of some representative dynamical processes. Multiplex Networks will appeal to students, researchers, and professionals within the fields of network science, graph theory, and data science.

Complex Networks & Their Applications XIII


Complex Networks & Their Applications XIII

Author: Hocine Cherifi

language: en

Publisher: Springer Nature

Release Date: 2025-03-27


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This book highlights cutting-edge research in network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XIII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2024). The carefully selected papers cover a wide range of theoretical topics such as network embedding and network geometry; community structure, network dynamics; diffusion, epidemics, and spreading processes; machine learning and graph neural networks, as well as all the main network applications, including social and political networks; networks in finance and economics; biological networks and technological networks.