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Kernel-Based Skyline Cardinality Estimation

Summary: Kernel-Based (KB) nonparametric skyline cardinality estimator; relaxes LS's independence, capturing inter-dimension correlations. Real-data experiments: KB outperforms Log Sampling in accuracy, maintains similar efficiency, and extends to k-dominant skylines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4205
Venue
SIGMOD
Year
2009
Pagerank
7.6249441e-05
Overall Rank
3,224 | 77.89%
DOI
10.1145/1559845.1559899

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhang_sigmod09,
        title = {{Kernel-Based Skyline Cardinality Estimation}},
        author = {Zhang, Zhenjie and Yang, Yin and Cai, Ruichu and Papadias, Dimitris and Tung, Anthony},
        series = {{SIGMOD} '09},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1559845.1559899},
        url = {https://dl.acm.org/doi/10.1145/1559845.1559899},
        year = {2009}
}

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