Efficient Size-Bounded Community Search, Revisited: Frameworks for Practical Improvements
Summary: Revisits Size-bounded Community Search (connected subgraph containing query q, size in [l,h], maximize min-degree) and introduces a branch-and-bound that efficiently isolates structurally compact candidate subsets. Three frameworks plus a heuristic, two reduction rules and query decomposition yield ~100× speedups and denser communities on 12 large graphs vs prior exact methods. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Yang Liu
- 2. Hejiao Huang
- 3. Kaiqiang Yu
- 4. Shengxin Liu
- 5. Cheng Long
- 6. Zhaoquan Gu
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