Abstract
The structure of large graphs can be revealed by partitio-ning graphs to smaller parts, which are easier to handle. In the paper we propose the use of core decomposition as an efficient approach for parti-tioning large graphs. On the selected subgraphs, computationally more intensive, clustering and blockmodeling can be used to analyze their internal structure. The approach is illustrated by an analysis of Snyder & Kick's world trade graph.
Cite
CITATION STYLE
Batagelj, V., Mrvar, A., & Zaveršnik, M. (1999). Partitioning approach to visualization of large graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1731, pp. 90–97). Springer Verlag. https://doi.org/10.1007/3-540-46648-7_9
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