Topic
Random walk closeness centrality
About: Random walk closeness centrality is a research topic. Over the lifetime, 547 publications have been published within this topic receiving 57559 citations.
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TL;DR: In this paper, the problem of constructing a flow network when the centrality at each vertex is given is considered, and the problem can be reduced to the previously known problem when a terminal capacity matrix is given.
Abstract: This paper considers the problem of constructing a flow network when the centrality at each vertex is given. Here, attention is given to a centrality function such that the centrality at a vertex under consideration is the sum of maximum flow values between it and all other vertices. It is a representative centrality function among those representing the centrality of each vertex in an undirected flow network in which edges have capacity. First, we introduce a necessary and sufficient condition wherein a given sequence is a centrality sequence for a flow network. Next, we present a procedure for determining a terminal capacity matrix of a flow network with a given centrality sequence. Furthermore, we determine a terminal capacity matrix of a flow network with a given centrality sequence such that the sum of edge capacity is minimum. From these discussions we can see that the problem of constructing a flow network when a centrality is given, can be reduced to the previously known problem of constructing a flow network when a terminal capacity matrix is given.
01 Feb 2016
TL;DR: This paper newly defines a concept of valued and directed workflow-supported social network, and its betweenness centrality analysis method and algorithms, and tries to apply the conventional method and the proposed method to an example workflow model respectively, and compare their betweennessCentrality analysis results.
Abstract: In this paper, we propose a novel analysis method and its algorithms to perform the betweenness centrality measurements on a valued and directed workflow-supported social network. The conventional workflow-supported social network model is to represent the existences of task transferring relationships among their performers by using a binary social network. However, it is necessary to consider not only the existences of task transferring relationships but also their quantities and directions in order to obtain much more effective and sophisticated analysis results. In conclusion, this paper newly defines a concept of valued and directed workflow-supported social network, and its betweenness centrality analysis method and algorithms. Especially, to verify the proposed method and algorithms, we try to apply the conventional method and the proposed method to an example workflow model respectively, and compare their betweenness centrality analysis results.