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Benchmarking Adaptive Multidimensional Indices

Summary: Benchmark comparing multidimensional adaptive-indexing methods across data types, distributions, sizes and workloads to expose relative strengths and failure modes. Proposes efficiency-enhancing tweaks and practical guidance for choosing/adapting methods in exploratory or evolving-data scenarios. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
14250
Venue
VLDB
Year
2025
Pagerank
5.0723324e-05
Overall Rank
11,052 | 24.44%
DOI
10.14778/3749646.3749709

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BibTeX Citation

@article{lampropoulos_vldb25,
        title = {{Benchmarking Adaptive Multidimensional Indices}},
        author = {Lampropoulos, Konstantinos and Zardbani, Fatemeh and Mamoulis, Nikos and Karras, Panagiotis},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {11},
        pages = {4505--4517},
        doi = {10.14778/3749646.3749709},
        url = {https://doi.org/10.14778/3749646.3749709},
        year = {2025}
}

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