net.librec.recommender.context.rating

Class TrustMFRecommender

java.lang.Object

net.librec.recommender.AbstractRecommender

net.librec.recommender.MatrixFactorizationRecommender

net.librec.recommender.SocialRecommender

net.librec.recommender.context.rating.TrustMFRecommender

All Implemented Interfaces:

Recommender

@ModelData(value={"isRating","trustmf","trusterUserTrusterFactors","trusterUserTrusteeFactors","trusteeUserTrusterFactors","trusteeUserTrusteeFactors","model"})
public class TrustMFRecommender
extends SocialRecommender

Yang et al., Social Collaborative Filtering by Trust, IJCAI 2013.

Author:

guoguibing and Keqiang Wang

Field Summary

Fields

Modifier and Type	Field and Description
protected java.lang.String	model model selection identifier
protected DenseMatrix	trusteeItemFactors trustee model
protected DenseMatrix	trusteeUserTrusteeFactors trustee model
protected DenseMatrix	trusteeUserTrusterFactors trustee model
protected DenseMatrix	trusterItemFactors truster model
protected DenseMatrix	trusterUserTrusteeFactors truster model
protected DenseMatrix	trusterUserTrusterFactors truster model

Fields inherited from class net.librec.recommender.SocialRecommender

regSocial, socialMatrix

Fields inherited from class net.librec.recommender.MatrixFactorizationRecommender

initMean, initStd, itemFactors, learnRate, maxLearnRate, numFactors, numIterations, regItem, regUser, userFactors

Fields inherited from class net.librec.recommender.AbstractRecommender

conf, context, decay, earlyStop, globalMean, isBoldDriver, isRanking, itemMappingData, lastLoss, LOG, loss, maxRate, minRate, numItems, numRates, numUsers, ratingScale, recommendedList, testMatrix, topN, trainMatrix, userMappingData, validMatrix, verbose

Constructor Summary

Constructors

Constructor and Description
TrustMFRecommender()

Method Summary

Methods

Modifier and Type	Method and Description
protected void	initTe()
protected void	initTr()
protected double	predict(int userIdx, int itemIdx) predict a specific rating for user userIdx on item itemIdx.
void	setup() setup init member method
protected void	trainModel() train Model
protected void	TrusteeMF() Build TrusteeMF model: We*Ve
protected void	TrusterMF() Build TrusterMF model: Br*Vr
protected void	updateLRate(int iter) This is the method used by the paper authors

Methods inherited from class net.librec.recommender.SocialRecommender

denormalize, normalize, predict

Methods inherited from class net.librec.recommender.AbstractRecommender

cleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, isConverged, loadModel, recommend, recommend, recommendRank, recommendRating, saveModel, setContext

Methods inherited from class java.lang.Object

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

Field Detail

trusterUserTrusterFactors

protected DenseMatrix trusterUserTrusterFactors

truster model

trusterUserTrusteeFactors

protected DenseMatrix trusterUserTrusteeFactors

truster model

trusterItemFactors

protected DenseMatrix trusterItemFactors

truster model

trusteeUserTrusterFactors

protected DenseMatrix trusteeUserTrusterFactors

trustee model

trusteeUserTrusteeFactors

protected DenseMatrix trusteeUserTrusteeFactors

trustee model

trusteeItemFactors

protected DenseMatrix trusteeItemFactors

trustee model

model

protected java.lang.String model

model selection identifier

Constructor Detail

TrustMFRecommender

public TrustMFRecommender()

Method Detail

setup

public void setup()
           throws LibrecException

Description copied from class: MatrixFactorizationRecommender

setup init member method

Overrides:

setup in class SocialRecommender

Throws:

LibrecException - if error occurs during setting up

initTr

protected void initTr()

initTe

protected void initTe()

trainModel

protected void trainModel()
                   throws LibrecException

Description copied from class: AbstractRecommender

train Model

Specified by:

trainModel in class AbstractRecommender

Throws:

LibrecException - if error occurs during training model

TrusterMF

protected void TrusterMF()
                  throws LibrecException

Build TrusterMF model: Br*Vr

Throws:

LibrecException - if error occurs

TrusteeMF

protected void TrusteeMF()
                  throws LibrecException

Build TrusteeMF model: We*Ve

Throws:

LibrecException - if error occurs

updateLRate

protected void updateLRate(int iter)

This is the method used by the paper authors

Overrides:

updateLRate in class MatrixFactorizationRecommender

Parameters:

iter - number of iteration

predict

protected double predict(int userIdx,
             int itemIdx)

Description copied from class: MatrixFactorizationRecommender

predict a specific rating for user userIdx on item itemIdx.

Overrides:

predict in class MatrixFactorizationRecommender

Parameters:

userIdx - user index

itemIdx - item index

Returns:

predictive rating for user userIdx on item itemIdx with bound