edu.uci.ics.jung.algorithms.scoring

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 Summary

Fields

Modifier and Type	Field and Description
protected double	alpha The probability of making a 'jump' at each step.
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.

Fields inherited from class edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorer

edge_weights, graph, hyperedges_are_self_loops, max_delta, max_iterations, output_reversed, tolerance, total_iterations

Constructor Summary

Constructors

Constructor and Description
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.
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.

Method Summary

Modifier and Type	Method and Description
double	getAlpha() Returns the probability of making a 'jump' (non-link-following step).
protected S	getVertexPrior(V v) Returns the prior probability for v.
com.google.common.base.Function<? super V,? extends S>	getVertexPriors() Returns a Function which maps each vertex to its prior probability.
void	initialize() Initializes the state of this instance.

Methods inherited from class edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorer

acceptDisconnectedGraph, afterStep, collectDisappearingPotential, done, evaluate, getAdjustedIncidentCount, getCurrentValue, getEdgeWeight, getEdgeWeights, getIterations, getMaxIterations, getOutputValue, getTolerance, getVertexScore, isDisconnectedGraphOK, setCurrentValue, setEdgeWeights, setHyperedgesAreSelfLoops, setMaxIterations, setOutputValue, setTolerance, step, swapOutputForCurrent, update, updateMaxDelta

Methods inherited from class java.lang.Object

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

Methods inherited from interface edu.uci.ics.jung.algorithms.scoring.VertexScorer

getVertexScore

Field Detail

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 Detail

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 Detail

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)