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Scalable Skyline Computation Using Object-based Space Partitioning

Summary: Dynamic object-based space-partitioning index accelerates skyline computation, integrated with sort-based skyline algorithms. Reduces CPU-bound dominance checks via bitwise operations; theory and experiments show scalable performance as size and dimensionality grow. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4203
Venue
SIGMOD
Year
2009
Pagerank
6.2133548e-05
Overall Rank
5,455 | 62.58%
DOI
10.1145/1559845.1559897

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhang_sigmod09,
        title = {{Scalable Skyline Computation Using Object-based Space Partitioning}},
        author = {Zhang, Shiming and Mamoulis, Nikos and Cheung, David W.},
        series = {{SIGMOD} '09},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1559845.1559897},
        url = {https://dl.acm.org/doi/10.1145/1559845.1559897},
        year = {2009}
}

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