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  2. Graph matching - Wikipedia

    en.wikipedia.org/wiki/Graph_matching

    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 ...

  3. Matching (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Matching_(graph_theory)

    A maximal matching is a matching M of a graph G that is not a subset of any other matching. A matching M of a graph G is maximal if every edge in G has a non-empty intersection with at least one edge in M. The following figure shows examples of maximal matchings (red) in three graphs. A maximum matching (also known as maximum-cardinality ...

  4. Matching (statistics) - Wikipedia

    en.wikipedia.org/wiki/Matching_(statistics)

    It was prominently criticized in economics by Robert LaLonde (1986), [7] who compared estimates of treatment effects from an experiment to comparable estimates produced with matching methods and showed that matching methods are biased. Rajeev Dehejia and Sadek Wahba (1999) reevaluated LaLonde's critique and showed that matching is a good ...

  5. Matching polytope - Wikipedia

    en.wikipedia.org/wiki/Matching_polytope

    The perfect matching polytope of a graph G, denoted PMP(G), is a polytope whose corners are the incidence vectors of the integral perfect matchings in G. [1]: 274 Obviously, PMP(G) is contained in MP(G); In fact, PMP(G) is the face of MP(G) determined by the equality:

  6. Perfect matching - Wikipedia

    en.wikipedia.org/wiki/Perfect_matching

    A perfect matching can only occur when the graph has an even number of vertices. A near-perfect matching is one in which exactly one vertex is unmatched. This can only occur when the graph has an odd number of vertices, and such a matching must be maximum. In the above figure, part (c) shows a near-perfect matching.

  7. Blossom algorithm - Wikipedia

    en.wikipedia.org/wiki/Blossom_algorithm

    The matching is constructed by iteratively improving an initial empty matching along augmenting paths in the graph. Unlike bipartite matching, the key new idea is that an odd-length cycle in the graph (blossom) is contracted to a single vertex, with the search continuing iteratively in the contracted graph.

  8. Matching in hypergraphs - Wikipedia

    en.wikipedia.org/wiki/Matching_in_hypergraphs

    A matching M is called perfect if every vertex v in V is contained in exactly one hyperedge of M. This is the natural extension of the notion of perfect matching in a graph. A fractional matching M is called perfect if for every vertex v in V, the sum of fractions of hyperedges in M containing v is exactly 1.

  9. Subgraph isomorphism problem - Wikipedia

    en.wikipedia.org/wiki/Subgraph_isomorphism_problem

    Subgraph isomorphism is a generalization of both the maximum clique problem and the problem of testing whether a graph contains a Hamiltonian cycle, and is therefore NP-complete. [1] However certain other cases of subgraph isomorphism may be solved in polynomial time. [2] Sometimes the name subgraph matching is also used for the same problem ...