1998
DOI: 10.1006/jagm.1997.0898
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Isomorph-Free Exhaustive Generation

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Cited by 345 publications
(309 citation statements)
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“…We reject isomorphs among the visited one-factorizations using the framework in [7], which is an instantiation of the canonical augmentation technique developed by McKay [13]. In essence, we identify a canonical Aut(X )-orbit of seeds contained by a visited one-factorization X , and then check whether the seed (Π, T, S) from which X was extended is in the canonical orbit.…”
Section: The Classificationmentioning
confidence: 99%
“…We reject isomorphs among the visited one-factorizations using the framework in [7], which is an instantiation of the canonical augmentation technique developed by McKay [13]. In essence, we identify a canonical Aut(X )-orbit of seeds contained by a visited one-factorization X , and then check whether the seed (Π, T, S) from which X was extended is in the canonical orbit.…”
Section: The Classificationmentioning
confidence: 99%
“…The problem of enumerating (i.e., listing) all graphs in particular classes of graphs is one of the most fundamental and important issues in graph theory, and has been studied extensively [1,7,9,10,13,16]. Cataloguing graphs, i.e., making the complete of graphs in a particular class can be used in a various way: search for a possible counterexample to a mathematical conjecture; choosing the best graph among all candidate graphs; and experiment for measuring the average performance of a graph algorithm over all possible input graphs.…”
Section: Introductionmentioning
confidence: 99%
“…To avoid the increased complexity of subgraph enumeration (in the absence of an appropriate hashing scheme) our algorithm works by exhaustively searching for the instances of a single query graph in a network. (To find all motifs of a given size we couple this search with subgraph enumeration, using McKay's geng and directg tools [15]). Even though the subgraph isomorphism problem -finding a given graph as a subgraph of a larger network -is known to be NP-complete, several algorithmic improvements enable this search to be carried out effectively in practice, even for subgraphs up to 31 nodes (and potentially even more).…”
Section: Distinguishing Features Of the New Algorithmmentioning
confidence: 99%
“…Our method can be used to find all instances of subgraphs of a given size, similar to previous exhaustive methods. To do this, we generate all non-isomorphic graphs of a particular size using McKay's geng and directg tools [15]. Then for each graph, we evaluate its significance as above.…”
Section: Subgraph Evaluation and Network Motif Discoverymentioning
confidence: 99%
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