Link Prediction On Yelp
평가 지표
HR@10
nDCG@10
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | HR@10 | nDCG@10 | Paper Title | Repository |
|---|---|---|---|---|
| KGAT | 0.8762 | 0.6136 | KGAT: Knowledge Graph Attention Network for Recommendation | - |
| CFKG | 0.8729 | 0.5826 | Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation | - |
| KGCN | 0.8125 | 0.4668 | Knowledge Graph Convolutional Networks for Recommender Systems | - |
| PEAGAT | 0.9128 | 0.6641 | Metapath- and Entity-aware Graph Neural Network for Recommendation | - |
| HSRL (DW) | - | - | Learning Topological Representation for Networks via Hierarchical Sampling | - |
| NGCF | 0.8068 | 0.481 | Neural Collaborative Filtering vs. Matrix Factorization Revisited | - |
| Event2vec | - | - | Representation Learning for Heterogeneous Information Networks via Embedding Events | - |
| NFM | 0.8595 | 0.6062 | Neural Factorization Machines for Sparse Predictive Analytics | - |
| Metapath2Vec | 0.6307 | 0.402 | metapath2vec: Scalable Representation Learning for Heterogeneous Networks |
0 of 9 row(s) selected.