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Finding Near Neighbors Through Cluster Pruning

Summary: Cluster pruning: pick random leaders, partition points by nearest leader, and search only the clusters of the closest leader(s) (with optional recursion) to obtain approximate nearest neighbors. Formalizes cost–accuracy tradeoffs, gives provable guarantees under generalized Gaussian-mixtures, and demonstrates orders-of-magnitude query speedups with modest quality loss, outperforming p-spheres in RAM and external-memory settings. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1420
Venue
PODS
Year
2007
Pagerank
6.4577834e-05
Overall Rank
4,090 | 71.55%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
936 Framework for Evaluating Clustering Algorithms in Duplicate Detection 2009 VLDB 0.0001521549
2,024 ATLAS: A Probabilistic Algorithm for High Dimensional Similarity Search 2011 SIGMOD 9.7519678e-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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