Densest Subgraph in Streaming and MapReduce
Summary: Streaming algorithms for densest subgraph use O(log_{1+ε} n) passes and achieve a 2(1+ε)-approximation, while mapping naturally to parallel MapReduce. Extensive experiments on massive real graphs demonstrate practical scalability. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Bahman Bahmani (Stanford University)
- 2. Ravi Kumar (Yahoo)
- 3. Sergei Vassilvitskii (Yahoo)
BibTeX Citation
@article{bahmani_vldb12,
title = {{Densest Subgraph in Streaming and MapReduce}},
author = {Bahmani, Bahman and Kumar, Ravi and Vassilvitskii, Sergei},
journal = {PVLDB},
series = {{VLDB} '12},
volume = {5},
number = {5},
pages = {454},
doi = {10.14778/2140436.2140442},
url = {https://doi.org/10.14778/2140436.2140442},
year = {2012}
}Incoming Citations (Sorted by Pagerank)
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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 |
|---|---|---|---|---|
| 130 | Discovering Large Dense Subgraphs in Massive Graphs | 2005 | VLDB | 0.0003029792 |
| 269 | 3-HOP: A High-Compression Indexing Scheme for Reachability Query | 2009 | SIGMOD | 0.00022625826 |
| 2,908 | Social Content Matching in MapReduce | 2011 | VLDB | 7.8645705e-05 |
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