Node Classification on DBLP (80% train)
94.1Macro F1MAGNN
Evaluation results
| Method | Links | ||
|---|---|---|---|
| MAGNNLearning paradigm=Semi-supervised, Classifier=Linear SVM2020.02 | 94.1 | 94.47 | |
| HANLearning paradigm=Semi-supervised, Classifier=Linear SVM2020.02 | 92.5 | 93.23 | |
| ESimLearning paradigm=Unsupervised, Classifier=Linear SVM2020.02 | 92.27 | 92.68 | |
| HERecLearning paradigm=Unsupervised, Classifier=Linear SVM2020.02 | 92.25 | 92.78 | |
| GATLearning paradigm=Semi-supervised, Classifier=Linear SVM2020.02 | 91.73 | 92.24 | |
| HDGI-CAvailable data=X, A2019.11 | 91.53 | 92.26 | |
| HDGI-AAvailable data=X, A2019.11 | 91.06 | 91.92 | |
| metapath2vecLearning paradigm=Unsupervised, Classifier=Linear SVM2020.02 | 90.86 | 91.31 | |
| HANAvailable data=X, A, Y2019.11 | 90.55 | 91 | |
| DGIAvailable data=X, A2019.11 | 90.52 | 91.5 | |
| GCNLearning paradigm=Semi-supervised, Classifier=Linear SVM2020.02 | 89.98 | 90.33 | |
| LINELearning paradigm=Unsupervised, Classifier=Linear SVM2020.02 | 89.51 | 89.96 | |
| node2vecLearning paradigm=Unsupervised, Classifier=Linear SVM2020.02 | 88.93 | 89.37 | |
| GATAvailable data=X, A, Y2019.11 | 84.76 | 85.4 | |
| GCNAvailable data=X, A, Y2019.11 | 83.08 | 83.83 | |
| RawAvailable data=X2019.11 | 81.52 | 83.25 | |
| M2VAvailable data=A2019.11 | 80.14 | 82.11 | |
| DW+FAvailable data=X, A2019.11 | 77.99 | 78.6 | |
| DWAvailable data=A2019.11 | 24.01 | 30.79 | |
| RGCNAvailable data=X, A, Y2019.11 | 22.12 | 21.75 |