public class EdgeBetweennessClusterer extends java.lang.Object implements GraphClusterer
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 and Description |
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EdgeBetweennessClusterer(int numEdgesToRemove)
Constructs a new clusterer for the specified graph.
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Modifier and Type | Method and Description |
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ClusterSet |
extract(ArchetypeGraph g)
Finds the set of clusters which have the strongest "community structure".
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java.util.List |
getEdgesRemoved()
Retrieves the list of all edges that were removed (assuming extract(...) was previously called.
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public EdgeBetweennessClusterer(int numEdgesToRemove)
numEdgesToRemove
- the number of edges to be progressively removed from the graphpublic ClusterSet extract(ArchetypeGraph g)
extract
in interface GraphClusterer
g
- the graphpublic java.util.List getEdgesRemoved()