Comparing Graph Clusterings: Set partition measures vs. Graph-aware measures
arXiv:1806.11494 · doi:10.1109/TPAMI.2020.3009862
Abstract
In this paper, we propose a family of graph partition similarity measures that take the topology of the graph into account. These graph-aware measures are alternatives to using set partition similarity measures that are not specifically designed for graph partitions. The two types of measures, graph-aware and set partition measures, are shown to have opposite behaviors with respect to resolution issues and provide complementary information necessary to assess that two graph partitions are similar.
arXiv comment15 pages, 8 figures
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