Effective Clustering for Large Multi-Relational Graphs
Summary: DEMM and DEMM+: a two-stage MRGC method that (i) learns node features by optimizing multi-relational Dirichlet energy and (ii) clusters by minimizing Dirichlet energy on the affinity graph. DEMM+ adds an efficient solver and a theory-backed transform to enable linear-time clustering without forming the N×N affinity, achieving high-quality, scalable clustering on million-node MRGs. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Xiaoyang Lin
- 2. Runhao Jiang
- 3. Renchi Yang
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| Rank | Cited Paper | Year | Venue | Pagerank |
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| 7,815 | Efficient and Effective Attributed Hypergraph Clustering via K-Nearest Neighbor Augmentation | 2023 | SIGMOD | 4.640481e-05 |
| 10,948 | Efficient High-Quality Clustering for Large Bipartite Graphs | 2024 | SIGMOD | 4.1905499e-05 |
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