Abstract
Exploiting the Discriminating Power of the Eigenvector Centrality Measure to Detect Graph Isomorphism
Highlights
Graph isomorphism is one of the classical problems of graph theory for which there exist no deterministic polynomial-time algorithm and at the same time the problem has not been yet proven to be NP-complete
To minimize the computation time, the test graphs are subject to one or more precursor steps that could categorically discard certain pair of graphs as non-isomorphic
Though centrality measures have been widely used for problems related to complex network analysis [3], the degree centrality measure is the only common and most directly used centrality measure to test for graph isomorphism [1]
Summary
Graph isomorphism is one of the classical problems of graph theory for which there exist no deterministic polynomial-time algorithm and at the same time the problem has not been yet proven to be NP-complete. The rest of the paper is organized as follows: Section 2 explains the procedure to determine the Eigenvector Centrality (EVC) values of the vertices.
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