net.librec.recommender.cf.rating

Class AspectModelRecommender

java.lang.Object

net.librec.recommender.AbstractRecommender

net.librec.recommender.ProbabilisticGraphicalRecommender

net.librec.recommender.cf.rating.AspectModelRecommender

All Implemented Interfaces:

Recommender

public class AspectModelRecommender
extends ProbabilisticGraphicalRecommender

Latent class models for collaborative filtering

This implementation refers to the method proposed by Thomas et al. at IJCAI 1999.

Tempered EM: Thomas Hofmann, Latent class models for collaborative filtering , IJCAI. 1999, 99: 688-693.

Author:

guoguibin and Haidong Zhang

Field Summary

Fields

Modifier and Type	Field and Description
protected int	numTopics
protected com.google.common.collect.Table<java.lang.Integer,java.lang.Integer,java.util.Map<java.lang.Integer,java.lang.Double>>	Q
protected static double	smallValue
protected DenseMatrix	topicItemProbs
protected DenseMatrix	topicItemProbsSum
protected DenseVector	topicProbs
protected DenseVector	topicProbsMean
protected DenseVector	topicProbsMeanSum
protected DenseVector	topicProbsSum
protected DenseVector	topicProbsVariance
protected DenseVector	topicProbsVarianceSum
protected DenseMatrix	topicUserProbs
protected DenseMatrix	topicUserProbsSum

Fields inherited from class net.librec.recommender.ProbabilisticGraphicalRecommender

burnIn, numItems, numIterations, numStats, numUsers, sampleLag

Fields inherited from class net.librec.recommender.AbstractRecommender

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

Constructor Summary

Constructors

Constructor and Description
AspectModelRecommender()

Method Summary

Methods

Modifier and Type	Method and Description
protected void	eStep() parameters estimation: used in the training phase
protected void	estimateParams() estimate the model parameters
protected void	mStep() update the hyper-parameters
protected double	predict(int userIdx, int itemIdx) predict a specific rating for user userIdx on item itemIdx, note that the prediction is not bounded.
protected void	readoutParams() read out parameters for each iteration
protected void	setup() setup init member method
protected void	trainModel() train Model

Methods inherited from class net.librec.recommender.ProbabilisticGraphicalRecommender

isConverged

Methods inherited from class net.librec.recommender.AbstractRecommender

cleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, loadModel, predict, 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

topicUserProbs

protected DenseMatrix topicUserProbs

topicUserProbsSum

protected DenseMatrix topicUserProbsSum

topicItemProbs

protected DenseMatrix topicItemProbs

topicItemProbsSum

protected DenseMatrix topicItemProbsSum

topicProbs

protected DenseVector topicProbs

topicProbsSum

protected DenseVector topicProbsSum

topicProbsMean

protected DenseVector topicProbsMean

topicProbsMeanSum

protected DenseVector topicProbsMeanSum

topicProbsVariance

protected DenseVector topicProbsVariance

topicProbsVarianceSum

protected DenseVector topicProbsVarianceSum

numTopics

protected int numTopics

smallValue

protected static double smallValue

Q

protected com.google.common.collect.Table<java.lang.Integer,java.lang.Integer,java.util.Map<java.lang.Integer,java.lang.Double>> Q

Constructor Detail

AspectModelRecommender

public AspectModelRecommender()

Method Detail

setup

protected void setup()
              throws LibrecException

Description copied from class: ProbabilisticGraphicalRecommender

setup init member method

Overrides:

setup in class ProbabilisticGraphicalRecommender

Throws:

LibrecException - if error occurs during setting up

trainModel

protected void trainModel()
                   throws LibrecException

Description copied from class: AbstractRecommender

train Model

Overrides:

trainModel in class ProbabilisticGraphicalRecommender

Throws:

LibrecException - if error occurs during training model

eStep

protected void eStep()

Description copied from class: ProbabilisticGraphicalRecommender

parameters estimation: used in the training phase

Specified by:

eStep in class ProbabilisticGraphicalRecommender

mStep

protected void mStep()

Description copied from class: ProbabilisticGraphicalRecommender

update the hyper-parameters

Specified by:

mStep in class ProbabilisticGraphicalRecommender

readoutParams

protected void readoutParams()

Description copied from class: ProbabilisticGraphicalRecommender

read out parameters for each iteration

Overrides:

readoutParams in class ProbabilisticGraphicalRecommender

estimateParams

protected void estimateParams()

Description copied from class: ProbabilisticGraphicalRecommender

estimate the model parameters

Overrides:

estimateParams in class ProbabilisticGraphicalRecommender

predict

protected double predict(int userIdx,
             int itemIdx)
                  throws LibrecException

Description copied from class: AbstractRecommender

predict a specific rating for user userIdx on item itemIdx, note that the prediction is not bounded. It is useful for building models with no need to bound predictions.

Specified by:

predict in class AbstractRecommender

Parameters:

userIdx - user index

itemIdx - item index

Returns:

predictive rating for user userIdx on item itemIdx without bound

Throws:

LibrecException - if error occurs during predicting