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SotA/Knowledge Base/Recommendation Systems/MovieLens 1M

Recommendation Systems on MovieLens 1M

Metric: RMSE (lower is better)

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#Model↕RMSE▲Extra DataPaperDate↕Code
1GLocal-K0.8227NoGLocal-K: Global and Local Kernels for Recommend...2021-08-27Code
2Sparse FC0.824No--Code
3CF-NADE0.829NoA Neural Autoregressive Approach to Collaborativ...2016-05-31Code
4IMC-GAE0.829NoInductive Matrix Completion Using Graph Autoenco...2021-08-25Code
5I-AutoRec0.831No--Code
6GC-MC0.832NoGraph Convolutional Matrix Completion2017-06-07Code
7I-CFN0.8321NoHybrid Recommender System based on Autoencoders2016-06-24Code
8GHRS0.838NoGHRS: Graph-based Hybrid Recommendation System w...2021-11-06Code
9FedPerGNN0.839No--Code
10BST0.8401NoBehavior Sequence Transformer for E-commerce Rec...2019-05-15Code
11NNMF0.843NoNeural Network Matrix Factorization2015-11-19Code
12FedGNN0.848NoFedGNN: Federated Graph Neural Network for Priva...2021-02-09-
13IGMC0.857NoInductive Matrix Completion Based on Graph Neura...2019-04-26Code
14U-CFN0.8574NoHybrid Recommender System based on Autoencoders2016-06-24Code
15Factorized EAE0.86NoDeep Models of Interactions Across Sets2018-03-07Code
16Factorization with dictionary learning0.866NoDictionary Learning for Massive Matrix Factoriza...2016-05-03Code