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Index Intersection for High-Dimensional Range Queries

Summary: Team-based Indexing: build lightweight indices over medium-sized attribute groups and intersect them to produce candidate tuple IDs for high-dimensional, highly-selective range queries. 5-attribute Teams beat bitmaps (6–7× faster, 1.58–2.07× less storage for 85-D), shifting optimization from per-index accuracy to efficient intersection. (summarized by gpt-5-mini on Mar 13 2026)

Paper ID
14357
Venue
VLDB
Year
2026
Pagerank
4.1945683e-05
Overall Rank
10,314 | 28.25%
DOI
10.14778/3785297.3785315

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