3 research outputs found
Comparison of algorithms in graph partitioning
We first describe four recent methods to cluster vertices of an
undirected non weighted connected graph. They are all based on
very different principles. The fifth is a combination of classical
ideas in optimization applied to graph partitioning. We compare
these methods according to their ability to recover classes
initially introduced in random graphs with more edges within the
classes than between them