Modeling High-Dimensional Index Structures using Sampling
Summary: Proposes a sampling-based cost model to predict index-page accesses for high-dimensional structures—dimensionality-agnostic and able to preserve data clusters. Provides a general page-layout estimator with error compensation and a memory-efficient implementation that yields fast predictions, up to 100x faster than building/probing the full index. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Christian A. Lang (University of California Santa Barbara)
- 2. Ambuj K. Singh (University of California Santa Barbara)
BibTeX Citation
@inproceedings{lang_sigmod01,
title = {{Modeling High-Dimensional Index Structures using Sampling}},
author = {Lang, Christian A. and Singh, Ambuj K.},
series = {{SIGMOD} '01},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/375663.375716},
url = {https://dl.acm.org/doi/10.1145/375663.375716},
year = {2001}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,176 | Predicting Cost Amortization for Query Services | 2011 | SIGMOD | 6.3326746e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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|---|
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