Estimating the Selectivity of Spatial Queries Using the 'Correlation' Fractal Dimension
Summary: Estimates selectivity of range and spatial-join queries from real spatial data using the Correlation Dimension D2 to capture fractal structure. Neighbor counts follow a power law with exponent D2; provides biased-query formulas with a shape constant K_shape, achieving ~10% error vs 40–100% under uniformity. (summarized by gpt-5-nano on Feb 09 2026)
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