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IO-Top-k: Index-access Optimized Top-k Query Processing

Summary: IO-Top-k jointly optimizes sequential index-list scheduling and random score accesses in threshold algorithms, unlike prior work treating them separately. Knapsack-based ordering, random-access cost models, and probabilistic estimators substantially accelerate top-k processing. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
9653
Venue
VLDB
Year
2006
Pagerank
9.3804693e-05
Overall Rank
1,967 | 86.51%
DOI
-

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BibTeX Citation

@article{bast_vldb06,
        title = {{IO-Top-k: Index-access Optimized Top-k Query Processing}},
        author = {Bast, Holger and Majumdar, Debapriyo and Schenkel, Ralf and Theobald, Martin and Weikum, Gerhard},
        journal = {PVLDB},
        series = {{VLDB} '06},
        pages = {475--486},
        year = {2006}
}

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