Recommendation Systems on Douban

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RMSE 낮을수록 좋음

Rank	Model	RMSE	NDCG	Recall@20	AUC	HR@10	HR@100	PSP@10	nDCG@10	Extra Training Data	Paper	Code	Year
1	I-CFN	0.6911	–	–	–	–	–	–	–		Hybrid Recommender System based on Autoencoders	fstrub95/Autoencoders_cf · SJD1882/Big-Data-Recommender-Systems · jowoojun/collaborative_filtering_keras · +1	2016
2	U-CFN	0.7049	–	–	–	–	–	–	–		Hybrid Recommender System based on Autoencoders	fstrub95/Autoencoders_cf · SJD1882/Big-Data-Recommender-Systems · jowoojun/collaborative_filtering_keras · +1	2016
3	GRALS	0.714	–	–	–	–	–	–	–	✓	Collaborative Filtering with Graph Information: Consistency and Scalable Methods	rofuyu/exp-grmf-nips15 · nikrao/GRALS	2015
4	FedPerGNN	0.775	–	–	–	–	–	–	–		A federated graph neural network framework for privacy-preserving personalization	wuch15/fedpergnn	2022
5	FedGNN	0.79	–	–	–	–	–	–	–		FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation		2021
6	DGRec	–	0.195	0.1861	–	–	–	–	–		Session-based Social Recommendation via Dynamic Graph Attention Networks	DeepGraphLearning/RecommenderSystems · sparsh-ai/RecommenderSystems	2019
7	∞-AE	–	–	–	0.9523	0.2356	0.2837	0.0128	0.2494		Infinite Recommendation Networks: A Data-Centric Approach	Guang000/Awesome-Dataset-Distillation · AmazingDD/daisyRec · recsys-benchmark/daisyrec-v2.0 · +2	2022