Top-K Recommendation on Last.FM (test)
0.2724Recall@20RaDAR
Evaluation results
| Method | Links | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| RaDAR2026.03 | 0.2724 | — | — | — | — | 0.1992 | — | — | 0.3664 | 0.2309 | |
| AdaGCL2026.03 | 0.2603 | — | — | — | — | 0.1911 | — | — | 0.3531 | 0.2204 | |
| SGL2026.03 | 0.2427 | — | — | — | — | 0.1761 | — | — | 0.3405 | 0.2104 | |
| DirectAU2026.03 | 0.2422 | — | — | — | — | 0.1727 | — | — | 0.3356 | 0.2042 | |
| SHT2026.03 | 0.242 | — | — | — | — | 0.177 | — | — | 0.3235 | 0.2055 | |
| HCCF2026.03 | 0.241 | — | — | — | — | 0.1773 | — | — | 0.3232 | 0.2051 | |
| NCL2026.03 | 0.2353 | — | — | — | — | 0.1715 | — | — | 0.3252 | 0.2033 | |
| LightGCN2026.03 | 0.2349 | — | — | — | — | 0.1704 | — | — | 0.322 | 0.2022 | |
| GCCF2026.03 | 0.2222 | — | — | — | — | 0.1642 | — | — | 0.3083 | 0.1931 | |
| GCMC2026.03 | 0.2218 | — | — | — | — | 0.1714 | — | — | 0.3149 | 0.1897 | |
| NGCF2026.03 | 0.2081 | — | — | — | — | 0.1474 | — | — | 0.2944 | 0.1829 | |
| STGCN2026.03 | 0.2067 | — | — | — | — | 0.1558 | — | — | 0.294 | 0.1821 | |
| SLRec2026.03 | 0.1957 | — | — | — | — | 0.1442 | — | — | 0.2792 | 0.1737 | |
| BiasMF2026.03 | 0.1879 | — | — | — | — | 0.1362 | — | — | 0.266 | 0.1653 | |
| PinSage2026.03 | 0.169 | — | — | — | — | 0.1228 | — | — | 0.2402 | 0.1472 | |
| AutoR2026.03 | 0.1518 | — | — | — | — | 0.1114 | — | — | 0.2174 | 0.1336 | |
| NCF2026.03 | 0.113 | — | — | — | — | 0.0795 | — | — | 0.1693 | 0.0952 | |
| KGAT2019.05 | 0.087 | — | — | — | — | 0.1325 | — | — | — | — | |
| NFM2019.05 | 0.0829 | — | — | — | — | 0.1214 | — | — | — | — | |
| GC-MC2019.05 | 0.0818 | — | — | — | — | 0.1253 | — | — | — | — | |
| RippleNet2019.05 | 0.0791 | — | — | — | — | 0.1238 | — | — | — | — | |
| FM2019.05 | 0.0778 | — | — | — | — | 0.1181 | — | — | — | — | |
| CKE2019.05 | 0.0736 | — | — | — | — | 0.1184 | — | — | — | — | |
| CFKG2019.05 | 0.0723 | — | — | — | — | 0.1143 | — | — | — | — | |
| BPR-MF2019.06 | — | — | — | — | — | — | 0.1199 | 0.0916 | — | — | |
| CFKGKG embedding=TransE2019.06 | — | — | — | — | — | — | 0.1781 | 0.1226 | — | — | |
| CKEembedding dimension=642019.05 | — | 0.023 | 0.07 | 0.18 | 0.296 | — | — | — | — | — | |
| ConvE-RecKG embedding=ConvE2019.06 | — | — | — | — | — | — | 0.2426 | 0.1742 | — | — | |
| Ekarranking strategy=path probabilities2019.06 | — | — | — | — | — | — | 0.2201 | 0.1552 | — | — | |
| Ekar*ranking strategy=rewards2019.06 | — | — | — | — | — | — | 0.2483 | 0.1766 | — | — | |
| ItemKNN2019.06 | — | — | — | — | — | — | 0.0605 | 0.0511 | — | — | |
| KGNN-LS2019.05 | — | 0.044 | 0.122 | 0.277 | 0.37 | — | — | — | — | — | |
| KTUP2019.06 | — | — | — | — | — | — | 0.1891 | 0.1566 | — | — | |
| LibFMdimension={1, 1, 8}, training epochs=502019.05 | — | 0.03 | 0.103 | 0.263 | 0.33 | — | — | — | — | — | |
| LibFM + TransETransE dimension=322019.05 | — | 0.032 | 0.102 | 0.259 | 0.326 | — | — | — | — | — | |
| MKR2019.06 | — | — | — | — | — | — | 0.1447 | 0.085 | — | — | |
| PERmeta-paths=manually designed user-item-attribute-item2019.05 | — | 0.014 | 0.052 | 0.116 | 0.176 | — | — | — | — | — | |
| RippleNetd=16, H=32019.05 | — | 0.032 | 0.101 | 0.242 | 0.336 | — | — | — | — | — | |
| RippleNet2019.06 | — | — | — | — | — | — | 0.1008 | 0.0641 | — | — | |
| SVD2019.05 | — | 0.029 | 0.098 | 0.21 | 0.332 | — | — | — | — | — |