2004
DOI: 10.1007/978-3-540-27868-9_18
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An Error-Tolerant Approximate Matching Algorithm for Attributed Planar Graphs and Its Application to Fingerprint Classification

Abstract: Abstract. Graph edit distance is a powerful error-tolerant similarity measure for graphs. For pattern recognition problems involving large graphs, however, the high computational complexity makes it sometimes impossible to apply edit distance algorithms. In the present paper we propose an efficient algorithm for edit distance computation of planar graphs. Given graphs embedded in the plane, we iteratively match small subgraphs by locally optimizing structural correspondences. Eventually we obtain a valid edit … Show more

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Cited by 59 publications
(34 citation statements)
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“…Of the algorithms that we tested, the greedy algorithm and the exhaustive algorithm with pruning are general algorithms to solve recursive problems. The process heuristic algorithm is similar to Neuhaus and Bunke's planar graph matching algorithm [17]. The main difference is that their algorithm starts with a random pair of graph nodes for comparison, while we assume that business process models have source nodes and sink nodes and we start by mapping source nodes.…”
Section: Related Workmentioning
confidence: 99%
“…Of the algorithms that we tested, the greedy algorithm and the exhaustive algorithm with pruning are general algorithms to solve recursive problems. The process heuristic algorithm is similar to Neuhaus and Bunke's planar graph matching algorithm [17]. The main difference is that their algorithm starts with a random pair of graph nodes for comparison, while we assume that business process models have source nodes and sink nodes and we start by mapping source nodes.…”
Section: Related Workmentioning
confidence: 99%
“…In particular, we plan to consider other graph matching techniques in which grouping of activities could be done more effectively. One possibility is to adapt a technique for graph matching of planar graphs proposed by Neuhaus and Bunke [18], in which a mapping is constructured starting from a node and then exploring the neighbourhood of that node, at which point one could consider grouping activities together. Process models are generally planar graphs (particularly structured process models) and this property can be exploited to achieve better tradeoffs.…”
Section: Conclusion and Future Research Directionsmentioning
confidence: 99%
“…As an alternative, a number of suboptimal methods have been proposed to make the graph edit distance less computationally demanding and therefore usable in real applications. Some of these methods are based on local optimization [24]. A linear programming method to compute the graph edit distance with unlabelled edges is presented in [25].…”
Section: Graph Edit Distancementioning
confidence: 99%