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Effective Change Detection Using Sampling

Summary: Proposes three sampling-based download policies for change detection under limited bandwidth. Combines per-source sampling with adaptive prioritization, yielding up to twofold increases over frequency-based policies in experiments on synthetic and real data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9062
Venue
VLDB
Year
2002
Pagerank
5.4119882e-05
Overall Rank
8,556 | 41.30%
DOI
10.1016/B978-155860869-6/50052-4

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{cho_vldb02,
        title = {{Effective Change Detection Using Sampling}},
        author = {Cho, Junghoo and Ntoulas, Alexandros},
        journal = {PVLDB},
        series = {{VLDB} '02},
        doi = {10.1016/B978-155860869-6/50052-4},
        url = {https://doi.org/10.1016/B978-155860869-6/50052-4},
        year = {2002}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
12,528 SHARC: Framework for Quality-Conscious Web Archiving 2009 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

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

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