Clustering 1-dimensional periodic network using betweenness centrality
نویسندگان
چکیده
منابع مشابه
Clustering 1-dimensional periodic network using betweenness centrality
Background While the temporal networks have a wide range of applications such as opportunistic communication, there are not many clustering algorithms specifically proposed for them. Methods Based on betweenness centrality for periodic graphs, we give a clustering pseudo-polynomial time algorithm for temporal networks, in which the transit value is always positive and the least common multipl...
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Betweenness is a centrality measure based on shortest paths, widely used in complex network analysis. It is computationally-expensive to exactly determine betweenness; currently the fastest-known algorithm by Brandes requires O(nm) time for unweighted graphs and O(nm + n log n) time for weighted graphs, where n is the number of vertices and m is the number of edges in the network. These are als...
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ژورنال
عنوان ژورنال: Computational Social Networks
سال: 2016
ISSN: 2197-4314
DOI: 10.1186/s40649-016-0031-1