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Published in:
2009 | OriginalPaper | Chapter
Kernelization of Softassign and Motzkin-Strauss Algorithms
Authors : M. A. Lozano, F. Escolano
Published in: Bio-Inspired Systems: Computational and Ambient Intelligence
Publisher: Springer Berlin Heidelberg
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This paper reviews two continuous methods for graph matching: Softassign and Replicator Dynamics. These methods can be applied to non-attributed graphs, but considering only structural information results in a higher ambiguity in the possible matching solutions. In order to reduce this ambiguity, we propose to extract attributes from non-attributed graphs and embed them in the graph-matching cost function, to be used as a similarity measure between the nodes in the graphs. Then, we evaluate their performance within the reviewed graph-matching algorithms.