Towards Efficient Index Construction and Approximate Nearest Neighbor Search in High-Dimensional Spaces
Summary: LSH-APG combines lightweight LSH with proximity graphs to cut ANN index construction cost while preserving high-quality greedy search. Incremental insertion and cardinality-insensitive maintenance address graph-index evolution, outperforming existing graph methods empirically. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Xi Zhao (Hong Kong University of Science and Technology)
- 2. Yao Tian (Hong Kong University of Science and Technology)
- 3. Kai Huang (Hong Kong University of Science and Technology)
- 4. Bolong Zheng (Huazhong University of Science and Technology)
- 5. Xiaofang Zhou (Hong Kong University of Science and Technology)
BibTeX Citation
@article{zhao_vldb23,
title = {{Towards Efficient Index Construction and Approximate Nearest Neighbor Search in High-Dimensional Spaces}},
author = {Zhao, Xi and Tian, Yao and Huang, Kai and Zheng, Bolong and Zhou, Xiaofang},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {8},
pages = {1979--1991},
doi = {10.14778/3594512.3594527},
url = {https://doi.org/10.14778/3594512.3594527},
year = {2023}
}
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