Optimal Multi-Step k-Nearest Neighbor Search
Summary: Two-stage kNN search for high-dimensional, adaptable similarity functions. Novel multi-step algorithm guarantees the minimum candidate set, outperforming Korn et al. 1996 with up to 120× fewer candidates and 48× faster runtime. (summarized by gpt-5-nano on Feb 09 2026)
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,107 | What is the nearest neighbor in high dimensional spaces? | 2000 | VLDB | 9.5330494e-05 |
| 34 | Similarity Search in High Dimensions via Hashing | 1999 | VLDB | 0.00076637636 |
| 2,023 | Efficient Approximate Nearest Neighbor Search in Multi-dimensional Databases | 2023 | SIGMOD | 9.7544991e-05 |
| 9,933 | Efficient and Effective KNN Sequence Search with Approximate n-grams | 2014 | VLDB | 4.2500258e-05 |
| 1,542 | Efficient Search for the Top-k Probable Nearest Neighbors in Uncertain Databases | 2008 | VLDB | 0.00011456321 |
| 709 | Efficient Similarity Search and Classification via Rank Aggregation | 2003 | SIGMOD | 0.00017768547 |
| 6,164 | Similarity Search: A Matching Based Approach | 2006 | VLDB | 5.1733919e-05 |
| 4,070 | Efficient Reverse k-Nearest Neighbor Search in Arbitrary Metric Spaces | 2006 | SIGMOD | 6.4784181e-05 |
| 5,882 | Improving Adaptable Similarity Query Processing by Using Approximations | 1998 | VLDB | 5.2892937e-05 |
| 3,579 | Efficient k-NN Search on Vertically Decomposed Data | 2002 | SIGMOD | 6.9502303e-05 |