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Anytime Measures for Top-k Algorithms

Summary: Anytime measures for top-k queries on large multi-attribute data, examining TA and TA-Sorted. A probabilistic framework yields, at any moment, the confidence that the top-k is identified, enabling early stopping and runtime savings. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9832
Venue
VLDB
Year
2007
Pagerank
5.6779179e-05
Overall Rank
7,185 | 50.71%
DOI
10.1145/1325851.1325954

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{arai_vldb07,
        title = {{Anytime Measures for Top-k Algorithms}},
        author = {Arai, Benjamin and Das, Gautam and Gunopulos, Dimitrios and Koudas, Nick},
        journal = {PVLDB},
        series = {{VLDB} '07},
        pages = {914--925},
        doi = {10.1145/1325851.1325954},
        url = {https://doi.org/10.1145/1325851.1325954},
        year = {2007}
}

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