Local Algorithms for Hierarchical Dense Subgraph Discovery
Summary: Local, parallel algorithms for core, truss, and nucleus decompositions enable hierarchical dense-subgraph discovery without synchronization. Extends h-index to higher-order decompositions with convergence bounds, enabling local, scalable approximations. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ahmet Erdem Sarıyüce (State University of New York at Buffalo)
- 2. C. Seshadhri (University of California)
- 3. Ali Pinar (Sandia National Laboratories)
BibTeX Citation
@article{saryuce_vldb19,
title = {{Local Algorithms for Hierarchical Dense Subgraph Discovery}},
author = {Sarıyüce, Ahmet Erdem and Seshadhri, C. and Pinar, Ali},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {1},
pages = {43--56},
doi = {10.14778/3275536.3275540},
url = {https://doi.org/10.14778/3275536.3275540},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
Showing 21 of 21 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 102 | Truss Decomposition in Massive Networks | 2012 | VLDB | 0.00034255289 |
| 138 | Discovering Large Dense Subgraphs in Massive Graphs | 2005 | VLDB | 0.00029823423 |
| 189 | Querying K-Truss Community in Large and Dynamic Graphs | 2014 | SIGMOD | 0.00026114928 |
| 269 | 3-HOP: A High-Compression Indexing Scheme for Reachability Query | 2009 | SIGMOD | 0.00022786599 |
| 825 | K-Core Decomposition of Large Networks on a Single PC | 2016 | VLDB | 0.00013779895 |
| 1,018 | Dense Subgraph Maintenance under Streaming Edge Weight Updates for Real-time Story Identification | 2012 | VLDB | 0.0001263063 |
| 2,985 | Piggybacking on Social Networks | 2013 | VLDB | 7.8919874e-05 |
| 4,667 | Efficient Cohesive Subgraphs Detection in Parallel | 2014 | SIGMOD | 6.5768564e-05 |
| 5,468 | Ego-net Community Mining Applied to Friend Suggestion | 2016 | VLDB | 6.2073549e-05 |
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