net.librec.recommender.context.rating

Class TrustSVDRecommender

java.lang.Object

net.librec.recommender.AbstractRecommender

net.librec.recommender.MatrixFactorizationRecommender

net.librec.recommender.SocialRecommender

net.librec.recommender.context.rating.TrustSVDRecommender

All Implemented Interfaces:

Recommender

@ModelData(value={"isRating","trustsvd","userFactors","itemFactors","impItemFactors","userBiases","itemBiases","socialMatrix","trainMatrix"})
public class TrustSVDRecommender
extends SocialRecommender

Guo et al., TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings, AAAI 2015.

Author:

guoguibing and Keqiang Wang

Field Summary

Fields

Modifier and Type	Field and Description
protected static java.lang.String	cacheSpec Guava cache configuration
protected double	regBias bias regularization
protected com.google.common.cache.LoadingCache<java.lang.Integer,java.util.List<java.lang.Integer>>	userItemsCache user-items cache, user-trustee cache
protected com.google.common.cache.LoadingCache<java.lang.Integer,java.util.List<java.lang.Integer>>	userTrusteeCache user-items cache, user-trustee cache

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
TrustSVDRecommender()

Method Summary

Methods

Modifier and Type	Method and Description
protected double	predict(int userIdx, int itemIdx) predict a specific rating for user userIdx on item itemIdx.
protected double	predict(int userIdx, int itemIdx, boolean bounded) predict a specific rating for user userIdx on item itemIdx.
void	setup() initial the model
protected void	trainModel() train model process

Methods inherited from class net.librec.recommender.SocialRecommender

denormalize, normalize

Methods inherited from class net.librec.recommender.MatrixFactorizationRecommender

updateLRate

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

regBias

protected double regBias

bias regularization

userItemsCache

protected com.google.common.cache.LoadingCache<java.lang.Integer,java.util.List<java.lang.Integer>> userItemsCache

user-items cache, user-trustee cache

userTrusteeCache

protected com.google.common.cache.LoadingCache<java.lang.Integer,java.util.List<java.lang.Integer>> userTrusteeCache

user-items cache, user-trustee cache

cacheSpec

protected static java.lang.String cacheSpec

Guava cache configuration

Constructor Detail

TrustSVDRecommender

public TrustSVDRecommender()

Method Detail

setup

public void setup()
           throws LibrecException

initial the model

Overrides:

setup in class SocialRecommender

Throws:

LibrecException - if error occurs

trainModel

protected void trainModel()
                   throws LibrecException

train model process

Specified by:

trainModel in class AbstractRecommender

Throws:

LibrecException - if error occurs

predict

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

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

Throws:

LibrecException - if error occurs

predict

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

Description copied from class: AbstractRecommender

predict a specific rating for user userIdx on item itemIdx. It is useful for evalution which requires predictions are bounded.

Overrides:

predict in class SocialRecommender

Parameters:

userIdx - user index

itemIdx - item index

bounded - whether there is a bound

Returns:

predictive rating for user userIdx on item itemIdx with bound

Throws:

LibrecException - if error occurs during predicting