Package edu.uci.ics.jung.algorithms.cluster

Mechanisms for identifying clusters in graphs.

See: Description

Class Summary

Class	Description
BicomponentClusterer<V,E>	Finds all biconnected components (bicomponents) of an undirected graph.
EdgeBetweennessClusterer<V,E>	An algorithm for computing clusters (community structure) in graphs based on edge betweenness.
TestBicomponentClusterer
TestEdgeBetweennessClusterer
VoltageClusterer<V,E>	Clusters vertices of a Graph based on their ranks as calculated by VoltageScorer.
WeakComponentClusterer<V,E>	Finds all weak components in a graph as sets of vertex sets.
WeakComponentClustererTest

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

Mechanisms for identifying clusters in graphs. Where these clusters define disjoint sets of vertices, they may be used to define a VertexPartition for more convenient manipulation of the vertex/set relationships. Current clustering algorithms include:

• BicomponentClusterer: finds all subsets of vertices for which at least 2 vertices must be removed in order to disconnect the induced subgraphs.
• EdgeBetweennessClusterer: identifies vertex clusters by removing the edges of the highest 'betweenness' scores (see the importance/scoring package).
• VoltageClusterer: Clusters vertices based on their ranks as calculated by VoltageRanker.
• WeakComponentVertexClusterer: Clusters vertices based on their membership in weakly connected components of a graph.