Package org.nlpub.watset.graph

Class ChineseWhispers.Implementation<V,E>

java.lang.Object

org.nlpub.watset.graph.ChineseWhispers.Implementation<V,E>

Type Parameters:

V - the type of nodes in the graph

E - the type of edges in the graph

Enclosing class:

ChineseWhispers<V,E>

protected static class ChineseWhispers.Implementation<V,E>
extends Object

Actual implementation of Chinese Whispers.

Field Summary

Fields

Modifier and Type	Field	Description
protected org.jgrapht.Graph<V,E>	graph	The graph.
protected int	iterations	The number of iterations.
protected Map<V,Integer>	labels	The mapping of nodes to labels.
protected Random	random	The random number generator.
protected int	steps	The number of actual algorithm iterations.
protected NodeWeighting<V,E>	weighting	The node weighting approach.

Constructor Summary

Constructors

Constructor	Description
Implementation(org.jgrapht.Graph<V,E> graph, NodeWeighting<V,E> weighting, int iterations, Random random)	Create an instance of the Chinese Whispers clustering algorithm implementation.

Method Summary

Modifier and Type	Method	Description
org.jgrapht.alg.interfaces.ClusteringAlgorithm.Clustering<V>	compute()	Perform clustering with Chinese Whispers.
int	getIterations()	Return the number of iterations specified in the constructor
int	getSteps()	Return the number of iterations actually performed during ChineseWhispers.getClustering().
protected Map<Integer,Double>	score(V node)	Score the label weights in the given neighborhood graph, which is a subgraph of graph.
protected int	step(List<V> nodes)	Perform one iteration of the algorithm.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

graph

protected final org.jgrapht.Graph<V,E> graph

The graph.

weighting

protected final NodeWeighting<V,E> weighting

The node weighting approach.

iterations

protected final int iterations

The number of iterations.

random

protected final Random random

The random number generator.

labels

protected final Map<V,Integer> labels

The mapping of nodes to labels.

steps

protected int steps

The number of actual algorithm iterations.

Constructor Detail

Implementation

public Implementation(org.jgrapht.Graph<V,E> graph,
                      NodeWeighting<V,E> weighting,
                      int iterations,
                      Random random)

Create an instance of the Chinese Whispers clustering algorithm implementation.

Parameters:

graph - the graph

weighting - the node weighting approach

iterations - the number of iterations

random - the random number generator

Method Detail

compute

public org.jgrapht.alg.interfaces.ClusteringAlgorithm.Clustering<V> compute()

Perform clustering with Chinese Whispers.

Returns:

the clustering

step

protected int step(List<V> nodes)

Perform one iteration of the algorithm.

Parameters:

nodes - the list of nodes

Returns:

whether any label changed or not

score

protected Map<Integer,Double> score(V node)

Score the label weights in the given neighborhood graph, which is a subgraph of graph. This method sums the node weights corresponding to each label.

Parameters:

node - the target node

Returns:

a mapping of labels to sums of their weights

getIterations

public int getIterations()

Return the number of iterations specified in the constructor

Returns:

the number of iterations

getSteps

public int getSteps()

Return the number of iterations actually performed during ChineseWhispers.getClustering(). Should be no larger than the value of getIterations().

Returns:

the number of iterations