Scalable Community Detection via Parallel Correlation Clustering
Summary: Scalable shared-memory framework for community detection via LambdaCC (modularity and correlation clustering) with generalized sequential and parallel implementations. Achieves high-quality clustering on unweighted/weighted graphs with billions of edges and yields large speedups (up to 28x vs sequential), improving speed–quality trade-offs. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jessica Shi
- 2. Laxman Dhulipala
- 3. David Eisenstat
- 4. Jakub Łącki
- 5. Vahab Mirrokni
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,879 | The ParClusterers Benchmark Suite (PCBS): A Fine-Grained Analysis of Scalable Graph Clustering | 2025 | VLDB | 4.1945683e-05 |
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