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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)

Paper ID
1919
Venue
PODS
Year
2024
Pagerank
5.628924e-05
Overall Rank
7,662 | 46.75%
DOI
10.1145/3651589

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
3,460 Finding Locally Densest Subgraphs: A Convex Programming Approach 2022 VLDB 7.470212e-05
4,823 Anchored Densest Subgraph 2022 SIGMOD 6.5592921e-05
5,124 Discovering Polarization Niches via Dense Subgraphs with Attractors and Repulsers 2022 VLDB 6.4185009e-05
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