Multi-Probe LSH: Efficient Indexing for High-Dimensional Similarity Search
Summary: Multi-Probe LSH reduces LSH’s costly proliferation of hash tables by probing multiple promising buckets within each table. It preserves search quality and time efficiency while cutting space by an order of magnitude, outperforming entropy-based LSH. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Qin Lv (Princeton University)
- 2. William Josephson (Princeton University)
- 3. Zhe Wang (Princeton University)
- 4. Moses Charikar (Princeton University)
- 5. Kai Li (Princeton University)
BibTeX Citation
@article{lv_vldb07,
title = {{Multi-Probe LSH: Efficient Indexing for High-Dimensional Similarity Search}},
author = {Lv, Qin and Josephson, William and Wang, Zhe and Charikar, Moses and Li, Kai},
journal = {PVLDB},
series = {{VLDB} '07},
volume = {30},
number = {2},
pages = {950--961},
doi = {10.14778/1325851.1325870},
url = {https://doi.org/10.14778/1325851.1325870},
year = {2007}
}
Incoming Citations (Sorted by Pagerank)
Showing 47 of 47 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2 | R-Trees: A Dynamic Index Structure For Spatial Searching | 1984 | SIGMOD | 0.0020210012 |
| 21 | Similarity Search in High Dimensions via Hashing | 1999 | VLDB | 0.00056760516 |
| 46 | A Quantitative Analysis and Performance Study for Similarity-Search Methods in High-Dimensional Spaces | 1998 | VLDB | 0.00044853085 |
| 277 | The SR-tree: An Index Structure for High-Dimensional Nearest Neighbor Queries | 1997 | SIGMOD | 0.00022537944 |
| 1,778 | The A-tree: An Index Structure for High-Dimensional Spaces Using Relative Approximation | 2000 | VLDB | 9.7769047e-05 |
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