Steiner-Hardness: A Query Hardness Measure for Graph-Based ANN Indexes
Summary: Steiner-hardness: a graph-native, connection-based measure of query difficulty for graph-based ANN, modeling minimal query effort on a representative graph. Reducible to Directed Steiner Tree so DST solvers compute it efficiently; outperforms LID in predicting actual query effort and yields unbiased index rankings. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Zeyu Wang (Fudan University)
- 2. Qitong Wang (Université Paris Cité)
- 3. Xiaoxing Cheng (Tongji University)
- 4. Peng Wang (Fudan University)
- 5. Themis Palpanas (Université Paris Cité)
- 6. Wei Wang (Fudan University)
BibTeX Citation
@article{wang_vldb24,
title = {{Steiner-Hardness: A Query Hardness Measure for Graph-Based ANN Indexes}},
author = {Wang, Zeyu and Wang, Qitong and Cheng, Xiaoxing and Wang, Peng and Palpanas, Themis and Wang, Wei},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {13},
pages = {4668--4682},
doi = {10.14778/3704965.3704974},
url = {https://doi.org/10.14778/3704965.3704974},
year = {2024}
}
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