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SBSC: A fast Self-tuned Bipartite proximity graph-based Spectral Clustering

Summary: SBSC: self-tuned, parameter-free bipartite graph for spectral clustering with locality sparsification, selecting O(sqrt(N)) representatives. Bi-means/K-means pick reps in O(N log N); local neighbor search yields an O(N)-sized graph and O(N(K^2+log N)) clustering time, with faster, higher-quality results on large data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7305
Venue
SIGMOD
Year
2025
Pagerank
5.1725247e-05
Overall Rank
10,531 | 26.81%
DOI
10.1145/3725418

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

Rank Cited Paper Year Venue Pagerank
5,319 SCAR — Spectral Clustering Accelerated and Robustified 2022 VLDB 6.3363428e-05
6,833 A New Sparse Data Clustering Method Based On Frequent Items 2023 SIGMOD 5.8190903e-05
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