Dynamic Katz and related network measures
Dynamic Katz and related network measures
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DOI：
10.1016/j.laa.2022.08.022
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发表时间：
2022-09-26
影响因子：
1.1
通讯作者：
Wood, Ryan
中科院分区：
文献类型：
--
作者：
Arrigo, Francesca;Higham, Desmond J.;Wood, Ryan
我们研究了基于步行的时间有序网络序列的中心性度量。对于标准的动态行走计数的情况下，我们展示了如何推导和计算由解析函数引起的中心性度量。我们还证明了动态Katz中心，基于预解函数，具有独特的优势，允许计算完全在节点级别上进行。然后，我们考虑两种不同类型的回溯，并开发一个框架，用于捕获动态步行组合时，其中一个或两个是不允许的。(c)2022作者爱思唯尔公司出版这是一个在CC BY许可证下的开放获取文章（http：//creativecommons.org/licenses/by/4.0/）。
We study walk-based centrality measures for time-ordered network sequences. For the case of standard dynamic walk -counting, we show how to derive and compute centrality measures induced by analytic functions. We also prove that dynamic Katz centrality, based on the resolvent function, has the unique advantage of allowing computations to be performed entirely at the node level. We then consider two distinct types of backtracking and develop a framework for capturing dynamic walk combinatorics when either or both is disallowed.(c) 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).