期刊
PATTERN RECOGNITION
卷 39, 期 1, 页码 22-34出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2005.06.014
关键词
inexact graph matching; graph simplification; graph partition; graph spectral clustering; Fiedler vector
Although inexact graph-matching is a problem of potentially exponential complexity, the problem may be simplified by decomposing the graphs to be matched into smaller subgraphs. If this is done, then the process may cast into a hierarchical framework and hence rendered suitable for parallel computation. In this paper we describe a spectral method which can be used to partition graphs into nonoverlapping subgraphs. In particular, we demonstrate how the Fiedler-vector of the Laplacian matrix can be used to decompose graphs into non-overlapping neighbourhoods that can be used for the purposes of both matching and clustering. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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