This paper presents a new algorithm that was developed for graph isomorphism, the main goal being obtaining the correct results with the best execution times. The things described are the utility and domains of usage for the algorithm, the nomenclature, the input data, the preconditions and graph definitions, the access of GNS1 to the query graphs and the data graph, the implementation details for the algorithm structure, methods and pruning techniques, then a series of test cases, the system specifications, the acknowledgment, the conclusions and the references. Motif graph finding has gathered increased popularity due to its vast domain of applicability. GNS1 is a backtracking algorithm with new pruning techniques for reducing the search space. It returns to the user all occurrences of a query graph found in a data graph while at the same time having much lower execution times than the STwig [1] and VF2 [2–4] algorithms. The algorithms can be used in a multitude of domains.
CITATION STYLE
Gheorghica, R. I. (2022). The GNS1 Algorithm for Graph Isomorphism. In Lecture Notes in Electrical Engineering (Vol. 869, pp. 243–255). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-0019-8_19
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