public class PageRankWithPriors<V,E> extends AbstractIterativeScorerWithPriors<V,E,Double>
PageRank
Modifier and Type | Field and Description |
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protected double |
disappearing_potential
Maintains the amount of potential associated with vertices with no out-edges.
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alpha, vertex_priors
edge_weights, graph, hyperedges_are_self_loops, max_delta, max_iterations, output_reversed, tolerance, total_iterations
Constructor and Description |
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PageRankWithPriors(Hypergraph<V,E> graph,
com.google.common.base.Function<E,? extends Number> edge_weights,
com.google.common.base.Function<V,Double> vertex_priors,
double alpha)
Creates an instance with the specified graph, edge weights, vertex priors, and
'random jump' probability (alpha).
|
PageRankWithPriors(Hypergraph<V,E> graph,
com.google.common.base.Function<V,Double> vertex_priors,
double alpha)
Creates an instance with the specified graph, vertex priors, and
'random jump' probability (alpha).
|
Modifier and Type | Method and Description |
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protected void |
afterStep()
Cleans up after each step.
|
protected void |
collectDisappearingPotential(V v)
Collects the "disappearing potential" associated with vertices that have
no outgoing edges.
|
double |
update(V v)
Updates the value for this vertex.
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getAlpha, getVertexPrior, getVertexPriors, initialize
acceptDisconnectedGraph, done, evaluate, getAdjustedIncidentCount, getCurrentValue, getEdgeWeight, getEdgeWeights, getIterations, getMaxIterations, getOutputValue, getTolerance, getVertexScore, isDisconnectedGraphOK, setCurrentValue, setEdgeWeights, setHyperedgesAreSelfLoops, setMaxIterations, setOutputValue, setTolerance, step, swapOutputForCurrent, updateMaxDelta
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getVertexScore
protected double disappearing_potential
public PageRankWithPriors(Hypergraph<V,E> graph, com.google.common.base.Function<E,? extends Number> edge_weights, com.google.common.base.Function<V,Double> vertex_priors, double alpha)
graph
- the input graphedge_weights
- the edge weights, denoting transition probabilities from source to destinationvertex_priors
- the prior probabilities for each vertexalpha
- the probability of executing a 'random jump' at each steppublic PageRankWithPriors(Hypergraph<V,E> graph, com.google.common.base.Function<V,Double> vertex_priors, double alpha)
graph
- the input graphvertex_priors
- the prior probabilities for each vertexalpha
- the probability of executing a 'random jump' at each steppublic double update(V v)
step()
.update
in class AbstractIterativeScorer<V,E,Double>
v
- the vertex whose value is to be updatedprotected void afterStep()
super.afterStep
.afterStep
in class AbstractIterativeScorer<V,E,Double>
protected void collectDisappearingPotential(V v)
collectDisappearingPotential
in class AbstractIterativeScorer<V,E,Double>
v
- the vertex whose potential is being collectedCopyright © 2015. All rights reserved.