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An Efficient Algorithm for Distance-based Structural Graph Clustering

Summary: Proposes distance-based SCAN: similarity = ratio of neighbors within d; non-neighbors and edge weights influence clustering. Uses bottom-k sketches (ADS) for O(k) similarity estimates, with histogram pruning for scalable, approximate clustering. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6548
Venue
SIGMOD
Year
2023
Pagerank
4.3481263e-05
Overall Rank
9,368 | 34.83%
DOI
10.1145/3588725

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,159 Efficient Influential Community Search over Dynamic Graphs 2026 SIGMOD 4.1945683e-05
10,240 Effective Durable Community Search in Large Temporal Graph 2026 VLDB 4.1945683e-05
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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