Topic
Katz centrality
About: Katz centrality is a research topic. Over the lifetime, 601 publications have been published within this topic receiving 77858 citations.
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12 Dec 2013
1 citations
01 Feb 2016
TL;DR: This paper proposes an estimated ranking algorithm and analyzes the accuracy and average computation time of the proposed algorithm, which shows that the accuracy improves 47.5%, 29.44% and 82.40% in the sizes of network and rates of samples, respectively.
Abstract: A type of workflow affiliation network is one of the specialized social network types, which represents the associative relation between actors and activities. There are many methods on a workflow affiliation network measuring centralities such as degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. In particular, we are interested in the closeness centrality measurements on a workflow affiliation network discovered from enterprise workflow models, and we know that the time complexity problem is raised according to increasing the size of the workflow affiliation network. This paper proposes an estimated ranking algorithm and analyzes the accuracy and average computation time of the proposed algorithm. As a result, we show that the accuracy improves 47.5%, 29.44% in the sizes of network and the rates of samples, respectively. Also the estimated ranking algorithm`s average computation time improves more than 82.40%, comparison with the original algorithm, when the network size is 2400, sampling rate is 30%.
1 citations
Posted Content•
TL;DR: In this article, the authors proposed a methodology to generalize degree, closeness and betweenness centralities taking into account the variability of edge weights in the form of closed intervals (Interval-Weighted Networks).
Abstract: Centrality measures are used in network science to evaluate the centrality of vertices or the position they occupy in a network. There are a large number of centrality measures according to some criterion. However, the generalizations of the most well-known centrality measures for weighted networks, degree centrality, closeness centrality, and betweenness centrality have solely assumed the edge weights to be constants. This paper proposes a methodology to generalize degree, closeness and betweenness centralities taking into account the variability of edge weights in the form of closed intervals (Interval-Weighted Networks -- IWN). We apply our centrality measures approach to two real-world IWN. The first is a commuter network in mainland Portugal, between the 23 NUTS 3 Regions. The second focuses on annual merchandise trade between 28 European countries, from 2003 to 2015.
1 citations
Journal Article•
TL;DR: It is shown that the introduction of BC actually accelerates the increase of ranks, and GBC reflects the influences of different group sizes particularly for choosing multiple link weight changes.
Abstract: Traffic matrix estimation problem remains one of the research focus for network designer and administrator for many years,especially the traffic estimation of back-bone networks for ISPs.In this article,we introduce betweenness centrality as the measure index of candidate snapshots and group betweenness centrality(GBC) particularly for choosing multiple link weight changes.Our experiments show that the introduction of BC actually accelerates the increase of ranks,and GBC reflects the influences of different group sizes.Some considerations are suggested for further research.
1 citations
Posted Content•
TL;DR: In this article, the degree centrality, alter-based centrality and power for each node in a symmetric network were calculated. And the degree and alter centrality of each node were compared.
Abstract: module to calculate degree centrality, alter-based centrality and power, and beta centrality and power for each node in a symmetric network.
1 citations