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The case of exact graph matching is known as the graph isomorphism problem. [1] The problem of exact matching of a graph to a part of another graph is called subgraph isomorphism problem. Inexact graph matching refers to matching problems when exact matching is impossible, e.g., when the number of vertices in the two graphs are different. In ...
A maximum matching (also known as maximum-cardinality matching [2]) is a matching that contains the largest possible number of edges. There may be many maximum matchings. The matching number of a graph G is the size of a maximum matching. Every maximum matching is maximal, but not every maximal matching is a maximum matching.
The space usage is extremely competitive in practice with other state-of-the-art compressors, [5] and it also supports fast in-situ pattern matching. The memory accesses made by compressed suffix arrays and other compressed data structures for pattern matching are typically not localized, and thus these data structures have been notoriously ...
There is now an online qualifier consisting of five events: two from the popular brain-training site Lumosity, and three events from the online memory competition website Memory League. The two events from Lumosity have typically been Memory Match Overdrive and Rotation Matrix, while the events from Memory League have been Images, Names, and ...
The closely related problem of counting the number of isomorphic copies of a graph H in a larger graph G has been applied to pattern discovery in databases, [8] the bioinformatics of protein-protein interaction networks, [9] and in exponential random graph methods for mathematically modeling social networks.
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The matching polynomial of a graph G with n vertices is related to that of its complement by a pair of (equivalent) formulas. One of them is a simple combinatorial identity due to Zaslavsky (1981) . The other is an integral identity due to Godsil (1981) .
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