Package edu.uci.ics.jung.algorithms.scoring

Mechanisms for assigning values (denoting significance, influence, centrality, etc.) to graph elements based on topological properties.

See: Description

Interface Summary

Interface	Description
EdgeScorer<E,S>	An interface for algorithms that assign scores to edges.
VertexScorer<V,S>	An interface for algorithms that assign scores to vertices.

Class Summary

Class	Description
AbstractIterativeScorer<V,E,T>	An abstract class for algorithms that assign scores to vertices based on iterative methods.
AbstractIterativeScorerWithPriors<V,E,S>	An abstract class for iterative random-walk-based vertex scoring algorithms that have a fixed probability, for each vertex, of 'jumping' to that vertex at each step in the algorithm (rather than following a link out of that vertex).
BarycenterScorer<V,E>	Assigns scores to each vertex according to the sum of its distances to all other vertices.
BetweennessCentrality<V,E>	Computes betweenness centrality for each vertex and edge in the graph.
ClosenessCentrality<V,E>	Assigns scores to each vertex based on the mean distance to each other vertex.
DegreeScorer<V>	Assigns a score to each vertex equal to its degree.
DistanceCentralityScorer<V,E>	Assigns scores to vertices based on their distances to each other vertex in the graph.
EigenvectorCentrality<V,E>	Calculates eigenvector centrality for each vertex in the graph.
HITS<V,E>	Assigns hub and authority scores to each vertex depending on the topology of the network.
HITS.Scores	Maintains hub and authority score information for a vertex.
HITSWithPriors<V,E>	A generalization of HITS that permits non-uniformly-distributed random jumps.
KStepMarkov<V,E>	A special case of PageRankWithPriors in which the final scores represent a probability distribution over position assuming a random (Markovian) walk of exactly k steps, based on the initial distribution specified by the priors.
PageRank<V,E>	Assigns scores to each vertex according to the PageRank algorithm.
PageRankWithPriors<V,E>	A generalization of PageRank that permits non-uniformly-distributed random jumps.
VoltageScorer<V,E>	Assigns scores to vertices according to their 'voltage' in an approximate solution to the Kirchoff equations.

Package edu.uci.ics.jung.algorithms.scoring Description

Mechanisms for assigning values (denoting significance, influence, centrality, etc.) to graph elements based on topological properties. These include:

• BarycenterScorer: assigns a score to each vertex according to the sum of the distances to all other vertices
• ClosenessCentrality: assigns a score to each vertex based on the mean distance to each other vertex
• DegreeScorer: assigns a score to each vertex based on its degree
• EigenvectorCentrality: assigns vertex scores based on long-term probabilities of random walks passing through the vertex at time t
• PageRank: like EigenvectorCentrality, but with a constant probability of the random walk restarting at a uniform-randomly chosen vertex
• PageRankWithPriors: like PageRank, but with a constant probability of the random walk restarting at a vertex drawn from an arbitrary distribution
• HITS: assigns hubs-and-authorities scores to vertices based on complementary random walk processes
• HITSWithPriors: analogous to HITS (see PageRankWithPriors)
• VoltageScorer: assigns scores to vertices based on simulated current flow along edges