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  2. List of NP-complete problems - Wikipedia

    en.wikipedia.org/wiki/List_of_NP-complete_problems

    Graphs occur frequently in everyday applications. Examples include biological or social networks, which contain hundreds, thousands and even billions of nodes in some cases (e.g. Facebook or LinkedIn). 1-planarity [1] 3-dimensional matching [2] [3]: SP1 Bandwidth problem [3]: GT40 Bipartite dimension [3]: GT18

  3. Planarity testing - Wikipedia

    en.wikipedia.org/wiki/Planarity_testing

    A different method uses an inductive construction of 3-connected graphs to incrementally build planar embeddings of every 3-connected component of G (and hence a planar embedding of G itself). [19] The construction starts with K 4 and is defined in such a way that every intermediate graph on the way to the full component is again 3-connected ...

  4. Connectivity (graph theory) - Wikipedia

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

    The edge-connectivity for a graph with at least 2 vertices is less than or equal to the minimum degree of the graph because removing all the edges that are incident to a vertex of minimum degree will disconnect that vertex from the rest of the graph. [1] For a vertex-transitive graph of degree d, we have: 2(d + 1)/3 ≤ κ(G) ≤ λ(G) = d. [11]

  5. Force-directed graph drawing - Wikipedia

    en.wikipedia.org/wiki/Force-directed_graph_drawing

    Force-directed graph drawing algorithms assign forces among the set of edges and the set of nodes of a graph drawing.Typically, spring-like attractive forces based on Hooke's law are used to attract pairs of endpoints of the graph's edges towards each other, while simultaneously repulsive forces like those of electrically charged particles based on Coulomb's law are used to separate all pairs ...

  6. igraph - Wikipedia

    en.wikipedia.org/wiki/Igraph

    An example of a graph created using igraph, representing the email network of the Enron Corpus. The three most important properties of igraph that shaped its development are as follows: [4] igraph is capable of handling large networks efficiently; it can be productively used with a high-level programming language

  7. Graph (abstract data type) - Wikipedia

    en.wikipedia.org/wiki/Graph_(abstract_data_type)

    In computer science, a graph is an abstract data type that is meant to implement the undirected graph and directed graph concepts from the field of graph theory within mathematics. A graph data structure consists of a finite (and possibly mutable) set of vertices (also called nodes or points ), together with a set of unordered pairs of these ...

  8. Connected-component labeling - Wikipedia

    en.wikipedia.org/wiki/Connected-component_labeling

    We first assign different binary values to elements in the graph. The values "0~1" at the center of each of the elements in the following graph are the elements' values, whereas the "1,2,...,7" values in the next two graphs are the elements' labels. The two concepts should not be confused. 2. After the first pass, the following labels are ...

  9. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    So far, we have calculated values for all possible m[i, j], the minimum number of calculations to multiply a chain from matrix i to matrix j, and we have recorded the corresponding "split point" s[i, j]. For example, if we are multiplying chain A 1 ×A 2 ×A 3 ×A 4, and it turns out that m[1, 3] = 100 and s[1, 3] = 2, that means that the ...