A Model for the Prediction of R-tree Performance
Summary: Analytical cost model predicting R-tree (and variants) disk-accesses for range queries using only dataset statistics (volume and spatial density), so applicable before index construction. Validated on synthetic/real data with ~10–15% error, useful for spatial query optimization. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yannis Theodoridis (National Technical University of Athens)
- 2. Timos Sellis (National Technical University of Athens)
BibTeX Citation
@inproceedings{theodoridis_pods96,
address = {New York, NY, USA},
series = {{PODS} '96},
title = {{A Model for the Prediction of R-tree Performance}},
url = {https://dl.acm.org/doi/10.1145/237661.237705},
doi = {10.1145/237661.237705},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Theodoridis, Yannis and Sellis, Timos},
year = {1996}
}
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