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Durable Top-k Search in Document Archives

Summary: Durable top-k search over versioned document archives: identify objects that remain in the top-k across a time window. Two solutions: NRA-based adaptation and a faster shared-execution approach, plus an archival index with space-partitioning. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4336
Venue
SIGMOD
Year
2010
Pagerank
6.5186944e-05
Overall Rank
4,765 | 67.31%
DOI
10.1145/1807167.1807228

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{u_sigmod10,
        title = {{Durable Top-k Search in Document Archives}},
        author = {U, Leong Hou and Mamoulis, Nikos and Berberich, Klaus and Bedathur, Srikanta},
        series = {{SIGMOD} '10},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1807167.1807228},
        url = {https://dl.acm.org/doi/10.1145/1807167.1807228},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
6,761 Efficiently Answering Durability Prediction Queries 2021 SIGMOD 5.7822533e-05
7,934 Ranking Large Temporal Data 2012 VLDB 5.5181056e-05
8,575 LIT: Lightning-fast In-memory Temporal Indexing 2024 SIGMOD 5.4095946e-05
10,315 Fast Indexing for Temporal Information Retrieval 2026 SIGMOD 5.093636e-05
11,954 Durable Top-k Queries on Temporal Data 2018 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

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