Double-Anonymous Sketch: Achieving Top-K-fairness for Finding Global Top-K Frequent Items
Summary: Proposes Double-Anonymous sketch to compute global top-K across disjoint streams with top-K-fairness. Leverages double-anonymity, hot panning, and early freezing; provides theoretical guarantees and extensive experiments showing substantial error reductions vs state-of-the-art; open-source code. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yikai Zhao (Peking University; Peng Cheng Laboratory)
- 2. Wenchen Han (Peking University)
- 3. Zheng Zhong (Peking University)
- 4. Yinda Zhang (Peking University)
- 5. Tong Yang (Peking University; Peng Cheng Laboratory)
- 6. Bin Cui (Peking University)
BibTeX Citation
@inproceedings{zhao_sigmod23,
title = {{Double-Anonymous Sketch: Achieving Top-K-fairness for Finding Global Top-K Frequent Items}},
author = {Zhao, Yikai and Han, Wenchen and Zhong, Zheng and Zhang, Yinda and Yang, Tong and Cui, Bin},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3588933},
url = {https://dl.acm.org/doi/10.1145/3588933},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,545 | SieveSketch: A Fine-grained and Adaptive Sketch Framework for Accurate Frequency Estimation | 2026 | SIGMOD | 4.9769913e-05 |
| 11,069 | CounterSnake: A lossless and generalized compression framework for diverse sketches | 2026 | VLDB | 4.9769913e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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