Recommendation Systems On Yelp2018
Metrics
NDCG@20
Recall@20
Results
Performance results of various models on this benchmark
Model Name | NDCG@20 | Recall@20 | Paper Title | Repository |
|---|---|---|---|---|
| MGDCF | 0.0575 | 0.0699 | MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering | |
| LightGCN | 0.0530 | 0.0649 | LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation | |
| SSCF | 0.0542 | 0.0664 | Sapling Similarity: a performing and interpretable memory-based tool for recommendation | |
| NESCL | 0.0611 | 0.0743 | Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering | - |
| SVD-AE | - | - | SVD-AE: Simple Autoencoders for Collaborative Filtering | |
| SimpleX | 0.0575 | 0.0701 | SimpleX: A Simple and Strong Baseline for Collaborative Filtering | |
| BSPM-LM | 0.0584 | 0.0713 | Blurring-Sharpening Process Models for Collaborative Filtering | |
| Turbo-CF | 0.0574 | 0.0693 | Turbo-CF: Matrix Decomposition-Free Graph Filtering for Fast Recommendation | |
| BSPM-EM | 0.0593 | 0.0720 | Blurring-Sharpening Process Models for Collaborative Filtering | |
| LT-OCF | 0.0549 | 0.0671 | LT-OCF: Learnable-Time ODE-based Collaborative Filtering |
0 of 10 row(s) selected.