DBScholar

Back to papers

Efficient Parallel Skyline Processing using Hyperplane Projections

Summary: Hyperplane projections partition multi-dimensional data for parallel skyline computation. Partitions yield small local skylines and enable efficient merging; outperforms prior parallel skyline methods across distributions and offers optimization insights. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4435
Venue
SIGMOD
Year
2011
Pagerank
5.8712039e-05
Overall Rank
6,467 | 55.64%
DOI
10.1145/1989323.1989333

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{kohler_sigmod11,
        title = {{Efficient Parallel Skyline Processing using Hyperplane Projections}},
        author = {Köhler, Henning and Yang, Jing and Zhou, Xiaofang},
        series = {{SIGMOD} '11},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1989323.1989333},
        url = {https://dl.acm.org/doi/10.1145/1989323.1989333},
        year = {2011}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers