Scalable Discovery of Best Clusters on Large Graphs

Summary: Top Graph Clusters (TopGC) probabilistically searches large edge-weighted directed graphs for their best clusters in linear time. Parallelizable, supports variable-size overlapping clusters, with a tunable memory parameter; up to 70% speedups and better scores on real-world benchmarks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 10118
Venue: VLDB
Year: 2010
Pagerank: 8.5710863e-05
Overall Rank: 2,541 | 82.35%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Kathy Macropol
2. Ambuj Singh

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
354	Local Search of Communities in Large Graphs	2014	SIGMOD	0.00026253833

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
34	Similarity Search in High Dimensions via Hashing	1999	VLDB	0.00076824554

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