An iterative algorithm for approximate median graph computation
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessRestricted access - publisher's policy
Recently, the median graph has been shown to be a good choice to obtain a representative of a given set of graphs. It has been successfully applied to graph-based classification and clustering. In this paper we exploit a theoretical property of the median, which has not yet been utilized in the past, to derive a new iterative algorithm for approximate median graph computation. Experiments done using five different graph databases show that the proposed approach yields, in four out of these five datasets, better medians than two of the previous existing methods.
CitationFerrer, M.; Bunke, H. An iterative algorithm for approximate median graph computation. A: International Conference on Pattern Recognition. "20th International Conference on Pattern Recognition (ICPR), 2010: 23-26 Aug. 2010, Istanbul, Turkey: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2010, p. 1562-1565.
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