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.
|
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