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Titlebook: Complex Networks and Their Applications VII; Volume 1 Proceedings Luca Maria Aiello,Chantal Cherifi,Luis M. Rocha Conference proceedings 20

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书目名称Complex Networks and Their Applications VII
副标题Volume 1 Proceedings
编辑Luca Maria Aiello,Chantal Cherifi,Luis M. Rocha
视频video
概述Presents the latest research on complex networks and their applications.Gathers the edited proceedings of the Seventh International Conference on Complex Networks and their Applications (COMPLEX NETWO
丛书名称Studies in Computational Intelligence
图书封面Titlebook: Complex Networks and Their Applications VII; Volume 1 Proceedings Luca Maria Aiello,Chantal Cherifi,Luis M. Rocha Conference proceedings 20
描述This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with a wealth of applications. It presents the peer-reviewed proceedings of the VII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2018), which was held in Cambridge on December 11–13, 2018. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure and network dynamics; diffusion, epidemics and spreading processes; and resilience and control; as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks..
出版日期Conference proceedings 2019
关键词Complex Networks; Complex Networks 2018; Network Models; Network Dynamics; Network Analysis
版次1
doihttps://doi.org/10.1007/978-3-030-05411-3
isbn_ebook978-3-030-05411-3Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Complex Networks and Their Applications VII978-3-030-05411-3Series ISSN 1860-949X Series E-ISSN 1860-9503
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Hecke Eigenvalues and Fourier Coefficientsy residents can reach even in the situation where roads are blocked by natural disasters. In the proposed centrality, we model the probabilistically occurring road blockage by the link cut of the graph, and quantify the degree of connectivity of each node by the expectation value of the number of re
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Basic Principles of the Calculation,shortest path centrality of each vertex in a graph as it aggregates contributions from possibly all vertex-pairs in the graph and not just from those vertex-pairs on whose geodesic path the vertex lies. As such, RWBC is more relevant in the context of information diffusion in virtual networks, such
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