Directional Queries: Making Top-k Queries More Effective in Discovering Relevant Results
Summary: Directional queries add a distance term to linear top-k, biasing toward balanced, skyline-like results aligned with attribute weights. Introduces four skyline-robustness and difficulty indicators and shows that the approach retrieves more relevant results with modest overhead on real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)
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