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LiteHST: A Tree Embedding based Method for Similarity Search

Summary: LiteHST: tree-embedding index for kNN under arbitrary metrics. Directly uses the HST tree for search (no embedding index) with a faster construction, lower time, and optimal distance bounds, plus reductions in distance computations; outperforms SOTA. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6600
Venue
SIGMOD
Year
2023
Pagerank
5.6298131e-05
Overall Rank
7,376 | 49.40%
DOI
10.1145/3588715

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zeng_sigmod23,
        title = {{LiteHST: A Tree Embedding based Method for Similarity Search}},
        author = {Zeng, Yuxiang and Tong, Yongxin and Chen, Lei},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3588715},
        url = {https://dl.acm.org/doi/10.1145/3588715},
        year = {2023}
}

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