nz.ac.waikato.mcennis.rat.graph.algorithm
Class AlgorithmFactory

java.lang.Object
  nz.ac.waikato.mcennis.rat.graph.algorithm.AlgorithmFactory

public class AlgorithmFactory
extends java.lang.Object

Class for generating an algorithm object without explicitly linking which one.

Constructor Summary

AlgorithmFactory()
Creates a new instance of AlgorithmFactory

Method Summary

Algorithm	create(java.util.Properties props) Creates an algorithm Algorithm is chosen via the 'algorithm' property.
java.lang.String[]	getKnownAggregatorModules()
java.lang.String[]	getKnownClusterModules()
java.lang.String[]	getKnownCollaborativeFilteringModules()
java.lang.String[]	getKnownDisplayModules()
java.lang.String[]	getKnownEvaluationModules()
java.lang.String[]	getKnownMachineLearningModules()
java.lang.String[]	getKnownOtherModules()
java.lang.String[]	getKnownPrestigeModules()
java.lang.String[]	getKnownSimilarityModules()
static AlgorithmFactory	newInstance() Singleton method for aquiring this instance

Methods inherited from class java.lang.Object

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

Constructor Detail

AlgorithmFactory

public AlgorithmFactory()

Creates a new instance of AlgorithmFactory

Method Detail

newInstance

public static AlgorithmFactory newInstance()

Singleton method for aquiring this instance

Returns:

AlgorithmFactory instance.

create

public Algorithm create(java.util.Properties props)

Creates an algorithm

Algorithm is chosen via the 'algorithm' property. Properties for each algorithm are described in the init method of each algorithm's JavaDoc.
The algorithms provided are:

• 'AddBasicBetweenessCentrality'
• 'AddBasicGeodesicPaths'
• 'AddBasicInterestLink'
• 'AddClosenessCentrality'
• 'AddDegreeCentrality'
• 'AddDegreeProperties'
• 'AddGeodesicProperties'
• 'AddMusicLinks'
• 'AddMusicRecommendations'
• 'AddMusicReferences'
• 'AddPageRankPrestige'
• 'EnumerateMaximalCliques'
• 'NaiveImplementClique'
• 'Evaluation'
• 'TrimEdgeUsers'
• 'HITSPrestige'
• 'ScalablePageRankPrestige'
• 'ScalableHITSPrestige'
• 'AddCombinedCloseness'
• 'OptimizedCloseness'
• 'OptimizedBetweeness'
• 'ExtractMusicCoverage'
• 'ExecuteWeka'
• 'OutputPageRank'
• 'RankingProperties'
• 'Difference'
• 'OutputDifference'
• 'Identify Bridges'
• 'Output Bridges By Cluster'
• 'Basic Display Graph'
• 'Colored By Property Graph'
• 'Display All'

Parameters:

props - mapof parameters for initialiing the algorithm

Returns:

newly constructed algorithm

getKnownOtherModules

public java.lang.String[] getKnownOtherModules()

getKnownSimilarityModules

public java.lang.String[] getKnownSimilarityModules()

getKnownAggregatorModules

public java.lang.String[] getKnownAggregatorModules()

getKnownPrestigeModules

public java.lang.String[] getKnownPrestigeModules()

getKnownClusterModules

public java.lang.String[] getKnownClusterModules()

getKnownCollaborativeFilteringModules

public java.lang.String[] getKnownCollaborativeFilteringModules()

getKnownDisplayModules

public java.lang.String[] getKnownDisplayModules()

getKnownMachineLearningModules

public java.lang.String[] getKnownMachineLearningModules()

getKnownEvaluationModules

public java.lang.String[] getKnownEvaluationModules()