Multi-level spectral graph partitioning method
A new method MSGP which enables multilevel and balanced partition
of regular and irregular graphs. The method has a spectral approximation and
shows that the eigenvectors of Laplacian of a graph have the multi-level and balanced
partitioning knowledge. Inspired by the Haar wavelets, MSGP reveals this hidden
knowledge in eigenvectors by using binary heap trees in the implementation stage. The
experimental works clearly demonstrate the superiority of MSGP over the seven existing
methods in terms of the correctness and performance.
Cite As
Talu, Muhammed Fatih. “Multi-Level Spectral Graph Partitioning Method.” Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no. 9, IOP Publishing, Sept. 2017, p. 093406, doi:10.1088/1742-5468/aa85ba.
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