Class AbstractIterativeScorerWithPriors<V,E,S>

java.lang.Object
edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorer<V,E,S>
edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorerWithPriors<V,E,S>
Type Parameters:
V - the vertex type
E - the edge type
S - the score type
All Implemented Interfaces:
VertexScorer<V,S>, IterativeContext
Direct Known Subclasses:
HITSWithPriors, PageRankWithPriors

public abstract class AbstractIterativeScorerWithPriors<V,E,S> extends AbstractIterativeScorer<V,E,S> implements VertexScorer<V,S>
An abstract class for iterative random-walk-based vertex scoring algorithms that have a fixed probability, for each vertex, of 'jumping' to that vertex at each step in the algorithm (rather than following a link out of that vertex).
  • Field Details

    • vertex_priors

      protected com.google.common.base.Function<? super V,? extends S> vertex_priors
      The prior probability of each vertex being visited on a given 'jump' (non-link-following) step.
    • alpha

      protected double alpha
      The probability of making a 'jump' at each step.
  • Constructor Details

    • AbstractIterativeScorerWithPriors

      public AbstractIterativeScorerWithPriors(Hypergraph<V,E> g, com.google.common.base.Function<? super E,? extends Number> edge_weights, com.google.common.base.Function<? super V,? extends S> vertex_priors, double alpha)
      Creates an instance for the specified graph, edge weights, vertex priors, and jump probability.
      Parameters:
      g - the graph whose vertices are to be assigned scores
      edge_weights - the edge weights to use in the score assignment
      vertex_priors - the prior probabilities of each vertex being 'jumped' to
      alpha - the probability of making a 'jump' at each step
    • AbstractIterativeScorerWithPriors

      public AbstractIterativeScorerWithPriors(Hypergraph<V,E> g, com.google.common.base.Function<V,? extends S> vertex_priors, double alpha)
      Creates an instance for the specified graph, vertex priors, and jump probability, with edge weights specified by the subclass.
      Parameters:
      g - the graph whose vertices are to be assigned scores
      vertex_priors - the prior probabilities of each vertex being 'jumped' to
      alpha - the probability of making a 'jump' at each step
  • Method Details

    • initialize

      public void initialize()
      Initializes the state of this instance.
      Overrides:
      initialize in class AbstractIterativeScorer<V,E,S>
    • getVertexPrior

      protected S getVertexPrior(V v)
      Returns the prior probability for v.
      Parameters:
      v - the vertex whose prior probability is being queried
      Returns:
      the prior probability for v
    • getVertexPriors

      public com.google.common.base.Function<? super V,? extends S> getVertexPriors()
      Returns a Function which maps each vertex to its prior probability.
      Returns:
      a Function which maps each vertex to its prior probability
    • getAlpha

      public double getAlpha()
      Returns the probability of making a 'jump' (non-link-following step).
      Returns:
      the probability of making a 'jump' (non-link-following step)