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Determining the Impact Regions of Competing Options in Preference Space

Summary: Introduces k-Shortlist Preference Region (kSPR) to identify regions in the d-dimensional preference space where a focal record ranks in the top-k under weighted-sum scoring. Proposes a computational-geometry, exact framework for efficient kSPR computation; benchmarks show up to three orders of magnitude speedup over a prior competitor built from earlier work. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5482
Venue
SIGMOD
Year
2017
Pagerank
5.3333957e-05
Overall Rank
9,010 | 38.19%
DOI
10.1145/3035918.3064044

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{tang_sigmod17,
        title = {{Determining the Impact Regions of Competing Options in Preference Space}},
        author = {Tang, Bo and Mouratidis, Kyriakos and Yiu, Man Lung},
        series = {{SIGMOD} '17},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3035918.3064044},
        url = {https://dl.acm.org/doi/10.1145/3035918.3064044},
        year = {2017}
}

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