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 final org.jgrapht.Graph<V,E>
    graph
    The graph.
    protected final int
    iterations
    The number of iterations.
    protected final Map<V,Integer>
    labels
    The mapping of nodes to labels.
    protected final Random
    random
    The random number generator.
    protected int
    steps
    The number of actual algorithm iterations.
    protected final 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 Details

    • 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 Details

    • 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 Details

    • 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