On Density-based Local Community Search
Summary: Proposes density-based Local Community Search (LCS) with seed set R, optimizing f(S) over induced subgraphs to blend density/conductance with R-inclusion, aiming for strongly local computation. Introduces a configuration-based framework; for density-based LCS, it identifies C_L as configurations enabling strongly local optimization and provides an LP-based, deployable solution. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yizhou Dai (University of Auckland)
- 2. Miao Qiao (University of Auckland)
- 3. Rong-Hua Li (Beijing Institute of Technology)
BibTeX Citation
@inproceedings{dai_pods24,
address = {New York, NY, USA},
series = {{PODS} '24},
title = {{On Density-based Local Community Search}},
url = {https://dl.acm.org/doi/10.1145/3651589},
doi = {10.1145/3651589},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Dai, Yizhou and Qiao, Miao and Li, Rong-Hua},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,226 | Efficient Anchored Densest Subgraph Discovery: Improved Time Complexity and Practical Performance | 2026 | SIGMOD | 5.093636e-05 |
| 10,280 | Periodic Community Search in Temporal Graphs: Time Series-based Methods | 2026 | SIGMOD | 5.093636e-05 |
| 10,349 | Budgeted Strong Community Search in Heterogeneous Graphs | 2026 | SIGMOD | 5.093636e-05 |
| 10,930 | Efficient k-Clique Densest Subgraph Discovery: Towards Bridging Practice and Theory | 2025 | VLDB | 5.093636e-05 |
| 10,941 | Effective and Efficient Community Search for Complex Network Semantics Capture: From Coarse-Grain to Fine-Grain | 2025 | VLDB | 5.093636e-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 |
|---|---|---|---|---|
| 3,148 | Finding Locally Densest Subgraphs: A Convex Programming Approach | 2022 | VLDB | 7.707548e-05 |
| 4,554 | Anchored Densest Subgraph | 2022 | SIGMOD | 6.6345929e-05 |
| 5,087 | Discovering Polarization Niches via Dense Subgraphs with Attractors and Repulsers | 2022 | VLDB | 6.3674344e-05 |
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