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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. Independent set (graph theory) - Wikipedia

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

    A maximum independent set is an independent set of largest possible size for a given graph . This size is called the independence number of and is usually denoted by (). [2] The optimization problem of finding such a set is called the maximum independent set problem.

  4. Glossary of graph theory - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_graph_theory

    1. This is the depth of a node plus 1, although some [12] define it instead to be synonym of depth. A node's level in a rooted tree is the number of nodes in the path from the root to the node. For instance, the root has level 1 and any one of its adjacent nodes has level 2. 2. A set of all node having the same level or depth. [12] line

  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. Maximal independent set - Wikipedia

    en.wikipedia.org/wiki/Maximal_independent_set

    Given a fixed ordering on the nodes and a factor δ∈(0,1], the following algorithm returns the same MIS: Initialize I to an empty set. While V is not empty: Select a factor δ∈(0,1]. Let P be the set of δn nodes that are first in the fixed ordering. Let W be a MIS on P using the totally parallel algorithm. Add W to I;

  7. Katz centrality - Wikipedia

    en.wikipedia.org/wiki/Katz_centrality

    A simple social network: the nodes represent people or actors and the edges between nodes represent some relationship between actors. Katz centrality computes the relative influence of a node within a network by measuring the number of the immediate neighbors (first degree nodes) and also all other nodes in the network that connect to the node under consideration through these immediate neighbors.

  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. Eigenvector centrality - Wikipedia

    en.wikipedia.org/wiki/Eigenvector_centrality

    In graph theory, eigenvector centrality (also called eigencentrality or prestige score [1]) is a measure of the influence of a node in a connected network.Relative scores are assigned to all nodes in the network based on the concept that connections to high-scoring nodes contribute more to the score of the node in question than equal connections to low-scoring nodes.