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Real Time Discovery of Dense Clusters in Highly Dynamic Graphs: Identifying Real World Events in Highly Dynamic Environments

Summary: Real-time event discovery from microblog streams via dense clusters in dynamic graphs; introduces the short-cycle prop. for evolving subgraphs. Proposes efficient clustering and a ranking function with proofs, validated on real data, achieving high precision/recall on dynamic graphs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10536
Venue
VLDB
Year
2012
Pagerank
4.7672834e-05
Overall Rank
7,308 | 49.17%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
4,208 Mining Bursting Core in Large Temporal Graphs 2022 VLDB 6.357214e-05
5,847 Spruce: A Fast yet Space-saving Structure for Dynamic Graph Storage 2024 SIGMOD 5.302174e-05
10,651 Triparts: Scalable Streaming Graph Partitioning to Enhance Community Structure 2025 VLDB 4.1945683e-05
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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
969 TwitterMonitor: Trend Detection over the Twitter Stream 2010 SIGMOD 0.00014942212
2,374 Seeking Stable Clusters in the Blogosphere 2007 VLDB 8.9452874e-05
12,183 EnBlogue – Emergent Topic Detection in Web 2.0 Streams 2011 SIGMOD 4.1945683e-05
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