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Query Refinement for Diverse Top-k Selection

Summary: Query refinement for top-k ORDER BY: minimally perturb predicates so results satisfy a user-defined diversity objective while preserving original intent. Proves hardness and gives an MILP-based optimizer plus scalability tricks for practical diverse top-k selection. (summarized by gpt-5.4-mini on May 24 2026)

Paper ID
6991
Venue
SIGMOD
Year
2024
Pagerank
5.8895166e-05
Overall Rank
6,389 | 56.17%
DOI
10.1145/3654969

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{campbell_sigmod24,
        title = {{Query Refinement for Diverse Top-k Selection}},
        author = {Campbell, Felix S. and Silberstein, Alon and Stoyanovich, Julia and Moskovitch, Yuval},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3654969},
        url = {https://dl.acm.org/doi/10.1145/3654969},
        year = {2024}
}

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