paper-with-me

Recommendation Systems 벤치마크

Recommendation Systems on YahooMusic Monti

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RMSE 낮을수록 좋음

18.9 23.69 28.47 33.26 38.04 2015-12 2026-11 GRALS — 38.0423 (2015-12-01) sRGCNN — 22.4149 (2017-04-22) GC-MC — 20.5 (2017-06-07) Factorized EAE — 20.0 (2018-03-07) IGMC — 19.1 (2019-04-26) MG-GAT — 18.9 (2020-09-20) GRALS — 38.0423 (2015-12-01) sRGCNN — 22.4149 (2017-04-22) GC-MC — 20.5 (2017-06-07) Factorized EAE — 20.0 (2018-03-07) IGMC — 19.1 (2019-04-26) MG-GAT — 18.9 (2020-09-20)
RankModel RMSE Extra Training Data PaperCodeYear
1 MG-GAT 18.9 ✓ Interpretable Recommender System With Heterogeneous Information: A Geometric Deep Learning Perspective zuirod/mg-gat 2020
2 IGMC 19.1 Inductive Matrix Completion Based on Graph Neural Networks muhanzhang/IGMC · zhoujf620/Motif-based-inductive-GNN-training · cheonsol-lee/IGMC_CX 2019
3 Factorized EAE 20.0 Deep Models of Interactions Across Sets mravanba/deep_exchangeable_tensors 2018
4 GC-MC 20.5 ✓ Graph Convolutional Matrix Completion dmlc/dgl · PreferredAI/cornac · riannevdberg/gc-mc · +14 2017
5 sRGCNN 22.4149 ✓ Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks fmonti/mgcnn · zuirod/mg-gat 2017
6 GRALS 38.0423 ✓ Collaborative Filtering with Graph Information: Consistency and Scalable Methods rofuyu/exp-grmf-nips15 · nikrao/GRALS 2015
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