Package es.uam.eps.ir.relison.sna.community.detection.modularity.balanced

Class RatioCutSpectralClustering<U>

java.lang.Object
es.uam.eps.ir.relison.sna.community.detection.modularity.balanced.SpectralClustering<U>
es.uam.eps.ir.relison.sna.community.detection.modularity.balanced.RatioCutSpectralClustering<U>
Type Parameters:
U - Type of the users.
All Implemented Interfaces:
CommunityDetectionAlgorithm<U>
public class RatioCutSpectralClustering<U>
extends SpectralClustering<U>
Community detection algorithm for balanced communities. It uses the ratio cut Laplacian.

Reference: R. Zafarani, M.A. Abassi, H. Liu. Social Media Mining: An Introduction. Chapter 6. 2014

  • Constructor Summary

    Constructors 
    Constructor Description
    RatioCutSpectralClustering​(int k)
    Constructor.

  • Method Summary

    Modifier and Type Method Description
    protected cern.colt.matrix.DoubleMatrix2D laplacian​(cern.colt.matrix.DoubleMatrix2D degree, cern.colt.matrix.DoubleMatrix2D adjacency)
    Computes the Laplacian matrix of a graph, given the degree and adjacency matrices.

    Methods inherited from class es.uam.eps.ir.relison.sna.community.detection.modularity.balanced.SpectralClustering

    detectCommunities

    Methods inherited from class java.lang.Object

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

  • Constructor Details

    • RatioCutSpectralClustering

      public RatioCutSpectralClustering​(int k)
      Constructor.
      Parameters:
      k - The number of clusters we want to find

  • Method Details

    • laplacian

      protected cern.colt.matrix.DoubleMatrix2D laplacian​(cern.colt.matrix.DoubleMatrix2D degree, cern.colt.matrix.DoubleMatrix2D adjacency)
      Description copied from class: SpectralClustering
      Computes the Laplacian matrix of a graph, given the degree and adjacency matrices.
      Specified by:
      laplacian in class SpectralClustering<U>
      Parameters:
      degree - the degree matrix of a graph
      adjacency - the adjacency matrix of a graph.
      Returns:
      the Laplacian matrix.