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java.lang.Objectedu.uci.ics.jung.algorithms.cluster.EdgeBetweennessClusterer
public class EdgeBetweennessClusterer
An algorithm for computing clusters (community structure) in graphs based on edge betweenness. [Note: The betweenness of an edge measure the extent to which that edge lies along shortest paths between all pairs of nodes.] Edges which are least central to communities are progressively removed until the communities have been adequately seperated. This algorithm works by iteratively following the 2 step process:
Running time is: O(kmn) where k is the number of edges to remove, m is the total number of edges, and n is the total number of vertices. For very sparse graphs the running time is closer to O(kn^2) and for graphs with strong community structure, the complexity is even lower.
This algorithm is a slight modification of the algorithm discussed below in that the number of edges to be removed is parameterized.
Constructor Summary | |
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EdgeBetweennessClusterer(int numEdgesToRemove)
Constructs a new clusterer for the specified graph. |
Method Summary | |
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ClusterSet |
extract(ArchetypeGraph g)
Finds the set of clusters which have the strongest "community structure". |
List |
getEdgesRemoved()
Retrieves the list of all edges that were removed (assuming extract(...) was previously called. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public EdgeBetweennessClusterer(int numEdgesToRemove)
numEdgesToRemove
- the number of edges to be progressively removed from the graphMethod Detail |
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public ClusterSet extract(ArchetypeGraph g)
extract
in interface GraphClusterer
g
- the graph
public List getEdgesRemoved()
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