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Ad-hoc Top-k Query Answering for Data Streams

Summary: Introduces a geometric-arrangement index for incrementally maintaining streaming tuples under arbitrary top-k scoring functions. Tuple pruning reduces state and manipulation, enabling efficient main-memory updates and ad-hoc query evaluation beyond pre-specified stream queries. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
9765
Venue
VLDB
Year
2007
Pagerank
7.5251856e-05
Overall Rank
3,317 | 77.25%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{das_vldb07,
        title = {{Ad-hoc Top-k Query Answering for Data Streams}},
        author = {Das, Gautam and Gunopulos, Dimitrios and Koudas, Nick and Sarkas, Nikos},
        journal = {PVLDB},
        series = {{VLDB} '07},
        pages = {183--194},
        year = {2007}
}

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