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Dimensional Testing for Reverse k-Nearest Neighbor Search

Summary: Dimensional testing uses intrinsic dimensionality to guide pruning and termination in approximate reverse k-nearest neighbor search. Compatible with any incremental NN index; reduces preprocessing while improving time/accuracy tradeoffs versus prior approaches. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11571
Venue
VLDB
Year
2017
Pagerank
4.4072367e-05
Overall Rank
9,025 | 37.22%
DOI
-

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Rank Citing Paper Year Venue Pagerank
7,654 LiteHST: A Tree Embedding based Method for Similarity Search 2023 SIGMOD 4.687476e-05
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