Centrality measures have been proved to be a salient computational science tool for
analyzing networks in the last two to three decades aiding many problems in the domain of …

Experts from several disciplines have been widely using centrality measures for analyzing
large as well as complex networks. These measures rank nodes/edges in networks by …

Betweenness centrality and k-path centrality are two important indices that are widely used
to analyze social, technological and information networks. In the current paper, first given a …

Betweenness Centrality (BC) is an important measure used widely in complex network
analysis, such as social network, web page search, etc. Computing the exact BC values is …

Centrality measures, erstwhile popular amongst the sociologists and psychologists, have
seen broad and increasing applications across several disciplines of late. Amongst a …

A large network frequently evolves in nature; hence, it is necessary to update the
betweenness centrality efficiently. Previously, the complexity for updated betweenness …

Centrality metrics are used to find important nodes in social networks. In the days of ever-
increasing social network sizes, it becomes more and more difficult to compute centrality …

Abstract Service Coverage Problem aims to find an ideal node for installing a service station
in a given network such that services requested from various nodes are satisfied while …

An important index widely used to analyze social and information networks is betweenness
centrality. In this paper, first given a directed network $ G $ and a vertex $ r\in V (G) $, we …

Graphs (networks) are an important tool to model data in different domains. Realworld
graphs are usually directed, where the edges have a direction and they are not symmetric …