Research Article
Variational Approach for Learning Community Structures
Table 4
Experimental results on Cora dataset.
| | NMI () | VI () | ACC () | Q () | CON () | TPR () |
| Spectral Clustering | 0.0651 | 2.0005 | 0.1252 | 0.0189 | 0.1909 | 0.6196 | Louvain | 0.4336 | 4.0978 | 0.0081 | 0.8142 | 0.0326 | 0.2821 | DeepWalk | 0.3796 | 2.7300 | 0.1626 | 0.6595 | 0.0396 | 0.4949 | node2vec | 0.3533 | 2.9947 | 0.1359 | 0.6813 | 0.1078 | 0.4902 |
| Stochastic Blockmodel | 0.0917 | 3.5108 | 0.1639 | 0.4068 | 0.4280 | 0.3376 | Stochastic Blockmodel (D.C.) | 0.1679 | 3.4547 | 0.1176 | 0.6809 | 0.1736 | 0.5112 | VGAE∗ + -means | 0.2384 | 3.3151 | 0.1033 | 0.6911 | 0.1615 | 0.4906 | VGAE + -means | 0.3173 | 3.1277 | 0.1589 | 0.6981 | 0.1517 | 0.5031 | VGAECD∗ | 0.2822 | 3.1606 | 0.1532 | 0.6674 | 0.1808 | 0.5076 | VGAECD | 0.5072 | 2.7787 | 0.1101 | 0.7029 | 0.1371 | 0.4987 |
|
|