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Finding Global Icebergs over Distributed Data Sets

Summary: Find global icebergs across many nodes despite items that are globally frequent but locally rare, avoiding prohibitive raw-data shipping. Introduce sampling and CountSketch-based distributed protocols with provable accuracy; CountSketch cuts communication by an order of magnitude while maintaining high accuracy. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1401
Venue
PODS
Year
2006
Pagerank
5.9914746e-05
Overall Rank
6,060 | 58.43%
DOI
10.1145/1142351.1142394

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhao_pods06,
        address = {New York, NY, USA},
        series = {{PODS} '06},
        title = {{Finding Global Icebergs over Distributed Data Sets}},
        url = {https://dl.acm.org/doi/10.1145/1142351.1142394},
        doi = {10.1145/1142351.1142394},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Zhao, Qi (George) and Ogihara, Mitsunori and Wang, Haixun and Xu, Jun (Jim)},
        year = {2006}
}

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