Modularity-based Hypergraph Clustering: Random Hypergraph Model, Hyperedge-cluster Relation, and Computation
Summary: Introduces HEM, a non-AON random hypergraph model, with PI for hyperedge-cluster quality. Proposes PIC and computation optimizations, achieving scalable modularity-based hypergraph clustering and up to 5 orders of magnitude faster than baselines. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Zijin Feng
- 2. Miao Qiao
- 3. Hong Cheng
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,827 | On Graph Representation for Attributed Hypergraph Clustering | 2025 | SIGMOD | 5.3113542e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,807 | A Model-based Approach to Attributed Graph Clustering | 2012 | SIGMOD | 8.0905959e-05 |
| 3,817 | A Particle-and-Density Based Evolutionary Clustering Method for Dynamic Networks | 2009 | VLDB | 6.730222e-05 |
| 9,952 | On Scalable Computation of Graph Eccentricities | 2022 | SIGMOD | 4.2405999e-05 |
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