Estimating the Selectivity of Spatial Queries Using the 'Correlation' Fractal Dimension
Summary: Uses correlation fractal dimension D₂—not uniformity/independence—to model neighbor counts as a power law, enabling spatial-join and density-biased range selectivity estimation. Shape-specific K_shape yields ~10% error versus 40–100% for uniformity. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Alberto Belussi (Polytechnic University of Milan)
- 2. Christos Faloutsos (AT&T; University of Maryland)
BibTeX Citation
@article{belussi_vldb95,
title = {{Estimating the Selectivity of Spatial Queries Using the 'Correlation' Fractal Dimension}},
author = {Belussi, Alberto and Faloutsos, Christos},
journal = {PVLDB},
series = {{VLDB} '95},
year = {1995}
}
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