Package net.librec.recommender.cf.ranking

Class Summary

Class	Description
AoBPRRecommender	AoBPR: BPR with Adaptive Oversampling
AspectModelRecommender	Latent class models for collaborative filtering
BPRRecommender	Rendle et al., BPR: Bayesian Personalized Ranking from Implicit Feedback, UAI 2009.
CLIMFRecommender	Shi et al., Climf: learning to maximize reciprocal rank with collaborative less-is-more filtering., RecSys 2012.
EALSRecommender	EALS: efficient Alternating Least Square for Weighted Regularized Matrix Factorization.
FISMaucRecommender	Kabbur et al., FISM: Factored Item Similarity Models for Top-N Recommender Systems, KDD 2013.
FISMrmseRecommender	Kabbur et al., FISM: Factored Item Similarity Models for Top-N Recommender Systems, KDD 2013.
GBPRRecommender	Pan and Chen, GBPR: Group Preference Based Bayesian Personalized Ranking for One-Class Collaborative Filtering, IJCAI 2013.
ItemBigramRecommender	Hanna M.
LDARecommender	Latent Dirichlet Allocation for implicit feedback: Tom Griffiths, Gibbs sampling in the generative model of Latent Dirichlet Allocation, 2002.
ListRankMFRecommender	Shi et al., List-wise learning to rank with matrix factorization for collaborative filtering, RecSys 2010.
PLSARecommender	Thomas Hofmann, Latent semantic models for collaborative filtering, ACM Transactions on Information Systems.
RankALSRecommender	Takacs and Tikk, Alternating Least Squares for Personalized Ranking , RecSys 2012.
RankSGDRecommender	Jahrer and Toscher, Collaborative Filtering Ensemble for Ranking, JMLR, 2012 (KDD Cup 2011 Track 2).
SLIMRecommender	Xia Ning and George Karypis, SLIM: Sparse Linear Methods for Top-N Recommender Systems, ICDM 2011.
WBPRRecommender	Gantner et al., Bayesian Personalized Ranking for Non-Uniformly Sampled Items, JMLR, 2012.
WRMFRecommender	WRMF: Weighted Regularized Matrix Factorization.