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Efficient and Generic Evaluation of Ranked Queries

Summary: Introduces a novel general sequential access scheme for top-k query evaluation that reduces random I/O and outperforms prior methods; extends to subspace and dynamic data. Also analyzes ranking queries (the rank of a given object) with exact and two approximate solutions, validated by extensive experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4416
Venue
SIGMOD
Year
2011
Pagerank
4.7798595e-05
Overall Rank
7,276 | 49.39%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,056 On the Complexity of Query Result Diversification 2013 VLDB 6.4883623e-05
12,111 Optimal Top-k Generation of Attribute Combinations based on Ranked Lists 2012 SIGMOD 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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