Table 3.
Node classification result of Citeseer
| Method | 10% | 30% | 50% | |||
|---|---|---|---|---|---|---|
| Mi-F1 | Ma-F1 | Mi-F1 | Ma-F1 | Mi-F1 | Ma-F1 | |
| DeepWalk | 0.5138 | 0.4711 | 0.5658 | 0.5301 | 0.5961 | 0.5415 |
| Node2Vec | 0.5302 | 0.4786 | 0.6233 | 0.5745 | 0.6317 | 0.5929 |
| GraRep | 0.4796 | 0.4613 | 0.5477 | 0.5098 | 0.5662 | 0.5026 |
| LINE | 0.5178 | 0.4825 | 0.5679 | 0.5249 | 0.6167 | 0.5733 |
| SDNE | 0.5013 | 0.4896 | 0.5691 | 0.5283 | 0.5877 | 0.5447 |
| TADW | 0.5939 | 0.5218 | 0.6361 | 0.5707 | 0.6631 | 0.5660 |
| GAE | 0.5912 | 0.5441 | 0.6439 | 0.5802 | 0.6451 | 0.5767 |
| VGAE | 0.6201 | 0.5638 | 0.6413 | 0.5789 | 0.6311 | 0.5799 |
| DANE | 0.6217 | 0.5740 | 0.6889 | 0.6495 | 0.7332 | 0.6832 |
| MRNL | 0.6833 | 0.6365 | 0.7176 | 0.6451 | 0.7301 | 0.6905 |