net.librec.recommender.context.ranking

Class SBPRRecommender

java.lang.Object

net.librec.recommender.AbstractRecommender

net.librec.recommender.MatrixFactorizationRecommender

net.librec.recommender.SocialRecommender

net.librec.recommender.context.ranking.SBPRRecommender

All Implemented Interfaces:

Recommender

@ModelData(value={"isRanking","sbpr","userFactors","itemFactors","itemBiases"})
public class SBPRRecommender
extends SocialRecommender

Social Bayesian Personalized Ranking (SBPR)

Zhao et al., Leveraging Social Connections to Improve Personalized Ranking for Collaborative Filtering, CIKM 2014.

Author:

guoguibing and Keqiang Wang

Field Summary

Fields

Modifier and Type	Field and Description
protected static java.lang.String	cacheSpec Guava cache configuration
protected float	regBias bias regularization
protected com.google.common.cache.LoadingCache<java.lang.Integer,java.util.List<java.lang.Integer>>	userItemsCache user-items cache, item-users 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
SBPRRecommender()

Method Summary

Methods

Modifier and Type	Method and Description
protected double	predict(int userIdx, int itemIdx) predict a specific ranking score for user userIdx on item itemIdx.
void	setup() setup init member method
protected void	trainModel() train Model

Methods inherited from class net.librec.recommender.SocialRecommender

denormalize, normalize, predict

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 float regBias

bias regularization

userItemsCache

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

user-items cache, item-users cache

cacheSpec

protected static java.lang.String cacheSpec

Guava cache configuration

Constructor Detail

SBPRRecommender

public SBPRRecommender()

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

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

predict

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

predict a specific ranking score for user userIdx on item itemIdx.

Overrides:

predict in class MatrixFactorizationRecommender

Parameters:

userIdx - user index

itemIdx - item index

Returns:

predictive ranking score for user userIdx on item itemIdx

Throws:

LibrecException - if error occurs