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  2. Node influence metric - Wikipedia

    en.wikipedia.org/wiki/Node_influence_metric

    It measures the diversity of self-avoiding walks which start from a given node. A walk on a network is a sequence of adjacent vertices; a self-avoiding walk visits (lists) each vertex at most once. The original work used simulated walks of length 60 to characterize the network of urban streets in a Brazilian city. [6]

  3. Closeness centrality - Wikipedia

    en.wikipedia.org/wiki/Closeness_centrality

    The number next to each node is the distance from that node to the square red node as measured by the length of the shortest path. The green edges illustrate one of the two shortest paths between the red square node and the red circle node. The closeness of the red square node is therefore 5/(1+1+1+2+2) = 5/7.

  4. Dijkstra's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra's_algorithm

    Find the path of minimum total length between two given nodes P and Q. We use the fact that, if R is a node on the minimal path from P to Q, knowledge of the latter implies the knowledge of the minimal path from P to R. is a paraphrasing of Bellman's Principle of Optimality in the context of the shortest path problem.

  5. Distance matrix - Wikipedia

    en.wikipedia.org/wiki/Distance_matrix

    In general, a distance matrix is a weighted adjacency matrix of some graph. In a network, a directed graph with weights assigned to the arcs, the distance between two nodes of the network can be defined as the minimum of the sums of the weights on the shortest paths joining the two nodes (where the number of steps in the path is bounded). [2]

  6. Shortest path problem - Wikipedia

    en.wikipedia.org/wiki/Shortest_path_problem

    Shortest path (A, C, E, D, F), blue, between vertices A and F in the weighted directed graph. In graph theory, the shortest path problem is the problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights of its constituent edges is minimized.

  7. Longest path problem - Wikipedia

    en.wikipedia.org/wiki/Longest_path_problem

    In graph theory and theoretical computer science, the longest path problem is the problem of finding a simple path of maximum length in a given graph.A path is called simple if it does not have any repeated vertices; the length of a path may either be measured by its number of edges, or (in weighted graphs) by the sum of the weights of its edges.

  8. Connectivity (graph theory) - Wikipedia

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

    This graph becomes disconnected when the right-most node in the gray area on the left is removed This graph becomes disconnected when the dashed edge is removed.. In mathematics and computer science, connectivity is one of the basic concepts of graph theory: it asks for the minimum number of elements (nodes or edges) that need to be removed to separate the remaining nodes into two or more ...

  9. Distance (graph theory) - Wikipedia

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

    The latter may occur even if the distance in the other direction between the same two vertices is defined. In the mathematical field of graph theory , the distance between two vertices in a graph is the number of edges in a shortest path (also called a graph geodesic ) connecting them.