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)
Incoming Non-self Citations Over Time
Authors
- 1. Felix S. Campbell (Ben Gurion University)
- 2. Alon Silberstein (Ben Gurion University)
- 3. Julia Stoyanovich (New York University)
- 4. Yuval Moskovitch (Ben Gurion University)
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}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,559 | Rodeo: Making Refinements for Diverse Top-k Queries | 2024 | VLDB | 5.2528121e-05 |
| 10,576 | Efficient Query Repair for Aggregate Constraints | 2026 | VLDB | 5.093636e-05 |
| 11,041 | GooseDB: A Database Engine that Optimally Refines Top-k Queries to Satisfy Representation Constraints | 2025 | VLDB | 5.093636e-05 |
| 13,310 | OmniTune: A Universal Framework for Query Refinement via LLMs | 2025 | SIGMOD | - |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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