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  2. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    In statistics and related fields, a similarity measure or similarity function or similarity metric is a real-valued function that quantifies the similarity between two objects. Although no single definition of a similarity exists, usually such measures are in some sense the inverse of distance metrics : they take on large values for similar ...

  3. Matching (graph theory) - Wikipedia

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

    A graph can only contain a perfect matching when the graph has an even number of vertices. A near-perfect matching is one in which exactly one vertex is unmatched. Clearly, a graph can only contain a near-perfect matching when the graph has an odd number of vertices, and near-perfect matchings are maximum matchings. In the above figure, part (c ...

  4. 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 ...

  5. Matching polynomial - Wikipedia

    en.wikipedia.org/wiki/Matching_polynomial

    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). There is a similar relation for a subgraph G of K m,n and its complement in K m,n. This ...

  6. Blossom algorithm - Wikipedia

    en.wikipedia.org/wiki/Blossom_algorithm

    INPUT: Graph G, matching M on G OUTPUT: augmenting path P in G or empty path if none found B01 function find_augmenting_path(G, M) : P B02 F ← empty forest B03 unmark all vertices and edges in G, mark all edges of M B05 for each exposed vertex v do B06 create a singleton tree { v} and add the tree to F B07 end for B08 while there is an ...

  7. Laplacian matrix - Wikipedia

    en.wikipedia.org/wiki/Laplacian_matrix

    where the zero and one entries of are treated as numerical, rather than logical as for simple graphs, values, explaining the difference in the results - for simple graphs, the symmetrized graph still needs to be simple with its symmetrized adjacency matrix having only logical, not numerical values, e.g., the logical sum is 1 v 1 = 1, while the ...

  8. Cosine similarity - Wikipedia

    en.wikipedia.org/wiki/Cosine_similarity

    In data analysis, cosine similarity is a measure of similarity between two non-zero vectors defined in an inner product space.Cosine similarity is the cosine of the angle between the vectors; that is, it is the dot product of the vectors divided by the product of their lengths.

  9. Induced subgraph - Wikipedia

    en.wikipedia.org/wiki/Induced_subgraph

    The induced subgraph isomorphism problem is a form of the subgraph isomorphism problem in which the goal is to test whether one graph can be found as an induced subgraph of another. Because it includes the clique problem as a special case, it is NP-complete.