Node Clustering on ACM
76.27ARIMCGC
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| MCGC2021.10 | 76.27 | 71.26 | 91.47 | 91.55 | — | |
| mWDKMethod Category=Optimization-free (OpF) methods2026.02 | 75.7 | 70.7 | 91.2 | — | — | |
| O2MAC2021.10 | 73.94 | 69.23 | 90.42 | 90.53 | — | |
| MCGCvariant=*2021.10 | 73.85 | 68.23 | 90.55 | 90.62 | — | |
| PANEMethod Category=Deep learning and random-walk methods2026.02 | 72.9 | 69.5 | 89.3 | — | — | |
| SCHOOL2024.12 | 72.7 | 69.6 | — | — | — | |
| HGMAE2024.12 | 72.6 | 69.7 | — | — | — | |
| DMGIattn2024.12 | 72.5 | 70.2 | — | — | — | |
| HDMI2024.12 | 72.3 | 69.5 | — | — | — | |
| HERO2024.12 | 71.8 | 68.8 | — | — | — | |
| HGCML2024.12 | 71.6 | 69.1 | — | — | — | |
| MAGIMethod Category=Deep learning and random-walk methods, Inference Type=End-to-end clustering2026.02 | 70.9 | 66.1 | 89.1 | — | — | |
| CPIM2024.12 | 70.8 | 68.6 | — | — | — | |
| HeCo2024.12 | 70.5 | 67.8 | — | — | — | |
| DMGI2024.12 | 70.2 | 67.8 | — | — | — | |
| NDLSMethod Category=Deep learning and random-walk methods, Approach=Optimization-free (OpF)2026.02 | 70.2 | 67.8 | 89.3 | — | — | |
| GSNNMethod Category=Deep learning and random-walk methods, Approach=GAE2026.02 | 70.1 | 65.8 | 88.9 | — | — | |
| O2MA2021.10 | 69.87 | 65.15 | 88.8 | 88.94 | — | |
| NDLSMethod Category=Deep learning and random-walk methods, Approach=GAE2026.02 | 68 | 63.7 | 87.6 | — | — | |
| DAEGCMethod Category=Deep learning and random-walk methods, Inference Type=End-to-end clustering2026.02 | 66.3 | 62.8 | 87.5 | — | — | |
| HANattention_level=dual-level (node and semantic)2019.03 | 64.39 | 61.56 | — | — | — | |
| WDKMethod Category=Optimization-free (OpF) methods2026.02 | 62.4 | 57.8 | 85.8 | — | — | |
| HANndattention_level=node-level only2019.03 | 61.48 | 60.99 | — | — | — | |
| GAT2019.03 | 60.43 | 57.29 | — | — | — | |
| HANsemattention_level=semantic-level only2019.03 | 59.45 | 61.05 | — | — | — | |
| WLMethod Category=Optimization-free (OpF) methods2026.02 | 58.6 | 55.6 | 83.7 | — | — | |
| AGCMethod Category=Optimization-free (OpF) methods2026.02 | 57.7 | 55.1 | 83.6 | — | — | |
| GAEMethod Category=Deep learning and random-walk methods2026.02 | 56 | 53.5 | 82.6 | — | — | |
| GAE2021.10 | 54.44 | 49.14 | 82.16 | 82.25 | — | |
| GCN2019.03 | 53.01 | 51.4 | — | — | — | |
| GSNNMethod Category=Deep learning and random-walk methods, Approach=Optimization-free (OpF)2026.02 | 51.9 | 50.3 | 80.2 | — | — | |
| HDGI-A2019.11 | 50.86 | 57.05 | — | — | — | |
| HDGI-C2019.11 | 49.48 | 54.35 | — | — | — | |
| PMNE2021.10 | 43.02 | 46.48 | 69.36 | 69.55 | — | |
| HERec2019.03 | 37.13 | 40.7 | — | — | — | |
| DeepWalk2024.12 | 35.3 | 41.6 | — | — | — | |
| DeepWalk2019.03 | 35.1 | 41.61 | — | — | — | |
| LINE2021.10 | 34.33 | 39.41 | 64.79 | 65.94 | — | |
| ESim2019.03 | 34.32 | 39.14 | — | — | — | |
| DGI2019.11 | 34.27 | 41.09 | — | — | — | |
| RMSC2021.10 | 33.12 | 39.73 | 63.15 | 57.46 | — | |
| HeCoClustering method=K-means2022.10 | 32.69 | 39.06 | — | — | — | |
| SHGPClustering method=K-means2022.10 | 32.63 | 39.42 | — | — | — | |
| DMGIClustering method=K-means2022.10 | 32.46 | 38.45 | — | — | — | |
| HDGIClustering method=K-means2022.10 | 32.34 | 39.13 | — | — | — | |
| DeepWalk+Ffeatures=node features included2019.11 | 31.2 | 32.54 | — | — | — | |
| Raw Feature2019.11 | 30.99 | 32.62 | — | — | — | |
| M2VClustering method=K-means2022.10 | 28.49 | 32.53 | — | — | — | |
| Metapath2vec2019.11 | 24.57 | 27.59 | — | — | — | |
| Mp2vec2024.12 | 21.1 | 21.4 | — | — | — | |
| metapath2vec2019.03 | 21 | 21.22 | — | — | — | |
| H-DCClustering method=K-means2022.10 | 19.75 | 18.6 | — | — | — | |
| DeepWalk2019.11 | 18.24 | 25.47 | — | — | — | |
| SWMC2021.10 | 8.38 | 47.09 | 38.31 | 1.8 | — | |
| GG2025.07 | 5.9 | — | — | — | 47.8 | |
| GNN2025.07 | 3.4 | — | — | — | 54 | |
| GEE2025.07 | 3.3 | — | — | — | 5.8 |