Computing A Well-Representative Summary of Conjunctive Query Results
Summary: Computes k-sized summaries of conjunctive query results under cohesion (k-center) and diversity. Leverages oracle-based access to avoid enumeration, yielding O(1)-approximation in near-linear time (in N, poly(k)) and a 2+ε-approximation for k-center on relational data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pankaj K. Agarwal (Duke University)
- 2. Aryan Esmailpour (University of Illinois Chicago)
- 3. Xiao Hu (University of Waterloo)
- 4. Stavros Sintos (University of Illinois Chicago)
- 5. Jun Yang (Duke University)
BibTeX Citation
@inproceedings{agarwal_pods24,
address = {New York, NY, USA},
series = {{PODS} '24},
title = {{Computing A Well-Representative Summary of Conjunctive Query Results}},
url = {https://dl.acm.org/doi/10.1145/3695835},
doi = {10.1145/3695835},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Agarwal, Pankaj K. and Esmailpour, Aryan and Hu, Xiao and Sintos, Stavros and Yang, Jun},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,719 | Subset Sampling over Joins | 2026 | PODS | 5.2319816e-05 |
| 10,153 | Faster Relational Algorithms Using Geometric Data Structures | 2026 | PODS | 5.093636e-05 |
| 10,176 | Clustering with Set Outliers and Applications in Relational Clustering | 2026 | PODS | 5.093636e-05 |
| 10,180 | Query Answering Under Volume-Based Diversity Functions | 2026 | PODS | 5.093636e-05 |
| 11,144 | Improved Approximation Algorithms for Relational Clustering | 2024 | PODS | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 10 | 11,144 | Improved Approximation Algorithms for Relational Clustering | 2024 | PODS |