Module org.jgrapht.core
Package org.jgrapht.alg.clustering

Class LabelPropagationClustering<V,​E>

  • Type Parameters:
    V - the graph vertex type
    E - the graph edge type
    All Implemented Interfaces:
    ClusteringAlgorithm<V>
    public class LabelPropagationClustering<V,​E>
extends java.lang.Object
implements ClusteringAlgorithm<V>
    A label propagation clustering algorithm.

    The algorithm is a near linear time algorithm capable of discovering communities in large graphs. It is described in detail in the following paper:

    • Raghavan, U. N., Albert, R., and Kumara, S. (2007). Near linear time algorithm to detect community structures in large-scale networks. Physical review E, 76(3), 036106.

    As the paper title suggests the running time is close to linear. The algorithm runs in iterations, each of which runs in $O(n + m)$ where $n$ is the number of vertices and $m$ is the number of edges. The authors found experimentally that in most cases, 95% of the nodes or more are classified correctly by the end of iteration 5. See the paper for more details.

    The algorithm is randomized, meaning that two runs on the same graph may return different results. If the user requires deterministic behavior, the random number generator can be provided by the constructor.

    Author:
    Dimitrios Michail

    • Constructor Detail

      • LabelPropagationClustering

        public LabelPropagationClustering​(Graph<V,​E> graph)
        Create a new clustering algorithm.
        Parameters:
        graph - the graph (needs to be undirected)

      • LabelPropagationClustering

        public LabelPropagationClustering​(Graph<V,​E> graph,
                                  java.util.Random rng)
        Create a new clustering algorithm.
        Parameters:
        graph - the graph (needs to be undirected)
        rng - random number generator

      • LabelPropagationClustering

        public LabelPropagationClustering​(Graph<V,​E> graph,
                                  int maxIterations)
        Create a new clustering algorithm.
        Parameters:
        graph - the graph (needs to be undirected)
        maxIterations - maximum number of iterations (zero means no limit)

      • LabelPropagationClustering

        public LabelPropagationClustering​(Graph<V,​E> graph,
                                  int maxIterations,
                                  java.util.Random rng)
        Create a new clustering algorithm.
        Parameters:
        graph - the graph (needs to be undirected)
        maxIterations - maximum number of iterations (zero means no limit)
        rng - random number generator