Graph Abstraction Based on Node Betweenness Centrality

Graph Abstraction Based on Node Betweenness Centrality

Автор: Arwa M. Aldabobi, Riad S. Jabri

Журнал: International Journal of Image, Graphics and Signal Processing @ijigsp

Статья в выпуске: 11 vol.11, 2019 года.

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There are many graph abstraction methods that are existed as solutions for problems of graphs visualization. Visualization problems include edge crossings and node occlusions that hide the potential existed patterns. The aim of this research is to abstract graphs using one of network analysis metrics which is node betweenness centrality. Betweenness centrality is calculated for all graph nodes. Graph abstraction is done by removing the nodes with their attached edges such that they have betweenness centrality lower than a certain examined threshold. Experiments have been conducted and results show that the proposed abstraction method can effectively reduce the complexity of the graph visualization in term of node degree. Modularity of clusters after filtering is decreased but the final graph visualization is simpler and more informative.

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Graph abstraction, Network analysis metrics, Nodes betweenness centrality, Degree, Modularity

Короткий адрес: https://sciup.org/15017046

IDR: 15017046   |   DOI: 10.5815/ijigsp.2019.11.02

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