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Comparing Graph Clusterings: Set Partition Measures vs. Graph-Aware Measures.
- Source :
- IEEE Transactions on Pattern Analysis & Machine Intelligence; Jun2021, Vol. 43 Issue 6, p2127-2132, 6p
- Publication Year :
- 2021
-
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 graphs. 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 compare graph partitions. [ABSTRACT FROM AUTHOR]
- Subjects :
- COMPUTER vision
PARALLEL algorithms
Subjects
Details
- Language :
- English
- ISSN :
- 01628828
- Volume :
- 43
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Pattern Analysis & Machine Intelligence
- Publication Type :
- Academic Journal
- Accession number :
- 150287140
- Full Text :
- https://doi.org/10.1109/TPAMI.2020.3009862