Node Clustering on Citeseer
54.1NMINIDDGCluster
Evaluation results
| Method | Links | |||||||
|---|---|---|---|---|---|---|---|---|
| NIDDGClusterClustering Time=77.2ms2024.05 | 54.1 | — | 63.3 | — | — | — | — | |
| DCSL-GNNobtained_in_this_work=true2026.06 | 47.74 | — | — | — | — | — | — | |
| WGCN2026.05 | 46.76 | 72.49 | 63.34 | — | — | — | — | |
| RCLG2026.05 | 46.16 | 71.04 | 65.92 | — | — | — | — | |
| CAHC2026.03 | 45.9 | 69.8 | 65.1 | — | 46.2 | — | — | |
| DCRN2024.03 | 45.86 | 70.86 | — | — | — | — | — | |
| PFGC2024.03 | 45.45 | 71.9 | — | — | — | — | — | |
| GIC2026.06 | 45.3 | — | — | — | — | — | — | |
| SCGC2024.03 | 45.25 | 71.02 | — | — | — | — | — | |
| R-DGAEInput=C&S2021.07 | 45 | 70.5 | — | — | 47.1 | — | — | |
| R-DGAEtype=Residual-DGAE2021.07 | 45 | 70.5 | — | — | 47.1 | — | — | |
| AGE2024.03 | 44.92 | 70.39 | — | — | — | — | — | |
| MCGC2026.05 | 44.87 | 70.97 | 61.89 | — | — | — | — | |
| SCGC2026.05 | 44.78 | 71.14 | 61.95 | — | — | — | — | |
| COLES-S2GCInput=Both2022.01 | 44.41 | 69.2 | 64.7 | — | — | — | — | |
| DGIInput=C&S2021.07 | 44.4 | 68.8 | — | — | 45 | — | — | |
| CCGC2024.03 | 44.33 | 69.84 | — | — | — | — | — | |
| AGEInput=C&S2021.07 | 44.3 | 70.1 | — | — | 45.4 | — | — | |
| DGCN2024.03 | 44.13 | 71.27 | — | — | — | — | — | |
| TriCL2026.03 | 44.1 | 67.6 | 62.1 | — | 45.1 | — | — | |
| FGC2024.03 | 44.02 | 69.01 | — | — | — | — | — | |
| MAGI2026.05 | 43.96 | 69.8 | 65.03 | — | — | — | — | |
| DFCN2024.03 | 43.9 | 69.5 | — | — | — | — | — | |
| SE-HSSL2026.03 | 43.8 | 68.2 | 62.5 | — | 43.3 | — | — | |
| R-DGAE2021.07 | 43.7 | 69.5 | — | — | 45.7 | — | — | |
| MVGRL2024.03 | 43.66 | 68.66 | — | — | — | — | — | |
| CGC2024.03 | 43.61 | 69.31 | — | — | — | — | — | |
| RAGC2026.03 | 43.5 | 69.4 | 61.9 | — | 44.3 | — | — | |
| MGCCN2026.06 | 43.2 | — | — | — | — | — | — | |
| COLES-SGCInput=Both2022.01 | 43.09 | 68.24 | 63.85 | — | — | — | — | |
| S2GCInput=Both2022.01 | 42.87 | 69.11 | 64.65 | — | — | — | — | |
| SSGC2024.03 | 42.87 | 69.11 | — | — | — | — | — | |
| MAGIMethod Category=Deep learning and random-walk methods, Inference Type=End-to-end clustering2026.02 | 42.8 | 69.3 | — | — | 44.5 | — | — | |
| AGC-DRR2026.05 | 42.67 | 67.71 | 63.64 | — | — | — | — | |
| AGC2026.05 | 42.61 | 68.43 | 63.8 | — | — | — | — | |
| mWDKMethod Category=Optimization-free (OpF) methods2026.02 | 42.6 | 67.2 | — | — | 41.1 | — | — | |
| SEComm2026.06 | 42.53 | — | — | — | — | — | — | |
| LatGCR2019.04 | 42.07 | 67.83 | 63.31 | — | — | — | — | |
| R-GMM-VGAEInput=C&S2021.07 | 42 | 68.9 | — | — | 43.9 | — | — | |
| R-GMM-VGAEtype=Residual-GMM-VGAE2021.07 | 42 | 68.9 | — | — | 43.9 | — | — | |
| DAEGCMethod Category=Deep learning and random-walk methods, Inference Type=End-to-end clustering2026.02 | 41.9 | 67.3 | — | — | 42.5 | — | — | |
| CommDGI2026.06 | 41.9 | — | — | — | — | — | — | |
| NDLSMethod Category=Deep learning and random-walk methods, Approach=Optimization-free (OpF)2026.02 | 41.7 | 66.7 | — | — | 40.6 | — | — | |
| MGAEInput=C&S2021.07 | 41.6 | 66.9 | — | — | 42.5 | — | — | |
| R-GMM-VGAE2021.07 | 41.5 | 68.4 | — | — | 43.6 | — | — | |
| PANEMethod Category=Deep learning and random-walk methods2026.02 | 41.5 | 66.7 | — | — | 40.9 | — | — | |
| AGCInput=Both2019.06 | 41.13 | 67 | 62.48 | — | — | — | — | |
| AGC2019.04 | 41.13 | 67 | 62.48 | — | — | — | — | |
| AGC2026.06 | 41.13 | — | — | — | — | — | — | |
| AGCInput=C&S2021.07 | 41.1 | 67 | — | — | 41.9 | — | — | |
| DGClusterClustering Time=119.6ms2024.05 | 41 | — | 32.2 | — | — | — | — | |
| DGAE2021.07 | 40.9 | 67.7 | — | — | 42.5 | — | — | |
| AGCMethod Category=Optimization-free (OpF) methods2026.02 | 40.9 | 67 | — | — | 42.1 | — | — | |
| GMM-VGAEInput=C&S2021.07 | 40.7 | 67.5 | — | — | 42.4 | — | — | |
| GMM-VGAE2021.07 | 40.7 | 67.5 | — | — | 42.4 | — | — | |
| WLMethod Category=Optimization-free (OpF) methods2026.02 | 40.7 | 66.7 | — | — | 41.6 | — | — | |
| WDKMethod Category=Optimization-free (OpF) methods2026.02 | 40.6 | 66.3 | — | — | 40.1 | — | — | |
| GSNNMethod Category=Deep learning and random-walk methods, Approach=Optimization-free (OpF)2026.02 | 40.3 | 67.6 | — | — | 42.8 | — | — | |
| DGI2026.03 | 40 | 63.8 | 55.7 | — | 38.6 | — | — | |
| MGAEInput=Both2019.06 | 39.75 | 63.56 | 39.49 | — | — | — | — | |
| MGAE2019.04 | 39.75 | 63.56 | 39.49 | — | — | — | — | |
| DAEGCInput=C&S2021.07 | 39.7 | 67.2 | — | — | 41 | — | — | |
| DNENC-Att2026.06 | 39.7 | — | — | — | — | — | — | |
| GMM-VGAE2021.07 | 39.5 | 66.3 | — | — | 41.1 | — | — | |
| DGAE2021.07 | 39.2 | 66.5 | — | — | 40.3 | — | — | |
| MCGC2024.03 | 39.11 | 64.76 | — | — | — | — | — | |
| COLES-GCNInput=Both, Protocol=Stiefel2022.01 | 38.9 | 65.17 | 60.85 | — | — | — | — | |
| SDCN2024.03 | 38.71 | 65.96 | — | — | — | — | — | |
| COLES-GCNInput=Both2022.01 | 37.54 | 63.28 | 59.17 | — | — | — | — | |
| NDLSMethod Category=Deep learning and random-walk methods, Approach=GAE2026.02 | 36.2 | 58.5 | — | — | 32.6 | — | — | |
| SDCN2026.05 | 35.55 | 62.03 | 58.16 | — | — | — | — | |
| FGC2026.05 | 35.34 | 61.2 | 57.76 | — | — | — | — | |
| ARGE2018.02 | 35 | 57.3 | 54.6 | 57.3 | 34.1 | — | — | |
| ARGEInput=Both2019.06 | 35 | 57.3 | 54.6 | — | — | — | — | |
| ARGEInput=C&S2021.07 | 35 | 57.3 | — | — | 34.1 | — | — | |
| ARGAE2021.07 | 35 | 57.3 | — | — | 34.1 | — | — | |
| ARGEInput=Both2022.01 | 35 | 57.3 | 54.6 | — | — | — | — | |
| ARGVAInput=C&S2021.07 | 33.8 | 58.1 | — | — | 30.1 | — | — | |
| DMON2024.05 | 33.7 | — | 43.2 | — | — | — | — | |
| DMoN2026.06 | 33.7 | — | — | — | — | — | — | |
| SGCInput=Both2022.01 | 32.9 | 52.77 | 63.9 | — | — | — | — | |
| R-ARVGAEtype=Residual-ARVGAE2021.07 | 32.5 | 59.4 | — | — | 31.4 | — | — | |
| TADWInput=C&S2021.07 | 32 | 52.9 | — | — | 28.6 | — | — | |
| R-ARVGAE2021.07 | 31.6 | 59.2 | — | — | 30.8 | — | — | |
| SDCN2024.05 | 31.4 | — | 41.9 | — | — | — | — | |
| K-means2018.02 | 30.5 | 54 | 40.9 | 40.5 | 27.9 | — | — | |
| TADW2018.02 | 29.1 | 45.5 | 41.4 | 31.2 | 22.8 | — | — | |
| GSNNMethod Category=Deep learning and random-walk methods, Approach=GAE2026.02 | 28.7 | 50.3 | — | — | 47.4 | — | — | |
| Louvainobtained_in_this_work=true2026.06 | 28.62 | — | — | — | — | — | — | |
| R-ARGAE2021.07 | 28.5 | 48.6 | — | — | 18.9 | — | — | |
| ARGAE2021.07 | 28.4 | 36.6 | — | — | 16.1 | — | — | |
| R-ARGAEtype=Residual-ARGAE2021.07 | 28.4 | 49.3 | — | — | 17.4 | — | — | |
| GAEMethod Category=Deep learning and random-walk methods2026.02 | 27.6 | 54.1 | — | — | 26.8 | — | — | |
| ACCpooling_type=dense, learning_signal=unsupervised2025.12 | 27 | — | — | — | — | — | — | |
| K-meansobtained_in_this_work=true2026.06 | 26.54 | — | — | — | — | — | — | |
| ARVGAE2021.07 | 26.3 | 51.5 | — | — | 22.7 | — | — | |
| ARVGE2018.02 | 26.1 | 54.4 | 52.9 | 54.9 | 24.5 | — | — | |
| ARVGEInput=Both2019.06 | 26.1 | 54.4 | 52.9 | — | — | — | — | |
| ARVGE2019.04 | 26.1 | 54.4 | 52.9 | — | — | — | — | |
| ARVGEInput=C&S2021.07 | 26.1 | 54.4 | — | — | 24.5 | — | — |