Clustering on DBLP
92.98AccuracyMCGC
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| MCGC2021.10 | 92.98 | 83.02 | 77.46 | 92.52 | |
| MCGCvariant=*2021.10 | 91.62 | 74.9 | 79.95 | 91.12 | |
| O2MAC2021.10 | 90.74 | 72.87 | 77.8 | 90.13 | |
| O2MA2021.10 | 90.4 | 72.57 | 77.05 | 89.76 | |
| RMSC2021.10 | 89.94 | 71.11 | 76.47 | 82.48 | |
| GAE2021.10 | 88.59 | 69.25 | 74.1 | 87.43 | |
| LINE2021.10 | 86.89 | 66.76 | 69.88 | 85.46 | |
| mWDKMethod Category=Optimization-free (OpF) methods2026.02 | 81.6 | 54.9 | 57.7 | — | |
| RCLG2026.05 | 80.32 | 50.76 | — | 79.98 | |
| PMNE2021.10 | 79.25 | 59.14 | 52.65 | 79.66 | |
| MAGI2026.05 | 78.86 | 49.72 | — | 78.55 | |
| PANEMethod Category=Deep learning and random-walk methods2026.02 | 76.6 | 48.7 | 47.1 | — | |
| MAGIMethod Category=Deep learning and random-walk methods, Inference Type=End-to-end clustering2026.02 | 76.4 | 47.3 | 47.9 | — | |
| FGC2026.05 | 73.65 | 42.51 | — | 73.31 | |
| DESEVenue=KDD’252026.06 | 73.41 | 41.19 | 43.17 | — | |
| AGREEVenue=Ours2026.06 | 72.46 | 39.12 | 41.24 | — | |
| MCGC2026.05 | 72.33 | 43.75 | — | 71.97 | |
| CAHC2026.03 | 72.3 | 63.9 | 58.2 | 70.4 | |
| MAGIVenue=KDD’242026.06 | 71.57 | 43.4 | 43.3 | — | |
| SCGC2026.05 | 68.23 | 39.86 | — | 68.02 | |
| AGCMethod Category=Optimization-free (OpF) methods2026.02 | 67.6 | 38.8 | 32.5 | — | |
| GSNNMethod Category=Deep learning and random-walk methods, Approach=Optimization-free (OpF)2026.02 | 67.5 | 40.6 | 37.3 | — | |
| GSNNMethod Category=Deep learning and random-walk methods, Approach=GAE2026.02 | 66.7 | 39.8 | 36.1 | — | |
| NDLSMethod Category=Deep learning and random-walk methods, Approach=GAE2026.02 | 66.4 | 39.1 | 35.5 | — | |
| TriCL2026.03 | 65.9 | 62.4 | 50.4 | 63.7 | |
| GAEMethod Category=Deep learning and random-walk methods2026.02 | 64.9 | 35.6 | 29.6 | — | |
| WLMethod Category=Optimization-free (OpF) methods2026.02 | 64.5 | 35.4 | 27.1 | — | |
| NDLSMethod Category=Deep learning and random-walk methods, Approach=Optimization-free (OpF)2026.02 | 62.9 | 35.5 | 30.8 | — | |
| CDCVenue=TNNLS’252026.06 | 62.54 | 33.5 | 27.5 | — | |
| AGC2026.05 | 62.38 | 32.15 | — | 62.12 | |
| HOSCPooler=HOSC2025.12 | 62.31 | — | — | — | |
| WGCN2026.05 | 62.05 | 31.34 | — | 62.62 | |
| WDKMethod Category=Optimization-free (OpF) methods2026.02 | 61.8 | 39.5 | 37 | — | |
| AGC-DRR2026.05 | 61.43 | 32.77 | — | 59.13 | |
| SDCN2026.05 | 56.31 | 23.64 | — | 55.74 | |
| ARVGAEVenue=IJCAI’182026.06 | 54.97 | 22.61 | 17.7 | — | |
| CCGCVenue=AAAI’232026.06 | 54.78 | 23.81 | 18.64 | — | |
| CONVERTVenue=MM’232026.06 | 54.52 | 22.33 | 17.81 | — | |
| EGAEVenue=TNNLS’222026.06 | 53.64 | 18.19 | 15.07 | — | |
| DMoNPooler=DMoN2025.12 | 52.34 | — | — | — | |
| MinCutPooler=MinCut2025.12 | 52.01 | — | — | — | |
| ACCPooler=ACC2025.12 | 50.67 | — | — | — | |
| DAEGCMethod Category=Deep learning and random-walk methods, Inference Type=End-to-end clustering2026.02 | 50.5 | 23.5 | 12.2 | — | |
| JBPoolPooler=JBPool2025.12 | 50.48 | — | — | — | |
| GAEVenue=Classical2026.06 | 46.1 | 19.71 | 5.78 | — | |
| DiffpoolPooler=Diffpool2025.12 | 45.54 | — | — | — | |
| SCDGNVenue=MM’232026.06 | 45.42 | 13.63 | 8.56 | — | |
| VGAER2026.05 | 44.54 | 11.57 | — | 43.35 | |
| DAEGCVenue=IJCAI’192026.06 | 43.36 | 11.41 | 10.4 | — | |
| Node2vec2026.03 | 39.91 | 24.2 | 9.63 | 38.05 | |
| DFCNVenue=AAAI’212026.06 | 38.91 | 8.11 | 6.63 | — | |
| GLACVenue=TAI’252026.06 | 36.62 | 6.02 | 5.45 | — | |
| K-MeansVenue=Classical2026.06 | 32.74 | 2.98 | 15.31 | — | |
| SWMC2021.10 | 32.53 | 1.9 | 1.59 | 28.08 |