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A maximum matching is one that contains as many edges of G as possible.
In this example, the maximum matching is found to be,, and, as shown in Figure 2 (d).
A matching of a graph is an independent subset of the edges set and a maximum matching is a matching with as many edges in it as possible.
If is a perfect matching, that is, the number of edges in a maximum matching is equal to the cardinality of worker set, the optimal assignment is obtained.
(There are various ways to find the maximum matching. See, e.g, [12].) A maximum matching is a matching with the largest possible number of edges.
If a maximum matching is needed for directed network graphs, the common strategy in the literature is to get the bipartite equivalent of the network graph and apply the Edmonds Karp or any other algorithm for determining maximum matching in bipartite graphs.
Similar(50)
Before the spurge in interest for social network analysis, the graphs considered for maximum matching are typically bipartite graphs wherein there exists two sets of vertices (with no edges between vertices in the same set) and the edges connect the vertices from one set to the other set.
The different words of the secret data are mapped on the chosen array, where maximum match is found, which obscured the data and start indices are noted down.
The template with the maximum match is chosen as the corresponding pitch value for the spectrum at time t 0 and the degree of match captured by the harmonicity variable H t) (see Eq. 2).
The maximum match is a combination of the following two factors: (1) the size of the common graph determined by mapping and (2) the aggregate sequence similarity between nodes mapped to one another.
A maximum weighted matching is a maximum matching such that the sum of the weights of the edges is maximum.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com