Minimally Factorizing the Provenance of Self-join Free Conjunctive Queries
Summary: Minimizes provenance factorization size for self-join-free conjunctive queries; NP-complete, but a PTIME class identified. ILP yields exact minimal factorization; MFMC offers fast approximations, linking factorizations to VEOs and minimal query plans. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Neha Makhija (Northeastern University)
- 2. Wolfgang Gatterbauer (Northeastern University)
BibTeX Citation
@inproceedings{makhija_pods24,
address = {New York, NY, USA},
series = {{PODS} '24},
title = {{Minimally Factorizing the Provenance of Self-join Free Conjunctive Queries}},
url = {https://dl.acm.org/doi/10.1145/3651605},
doi = {10.1145/3651605},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Makhija, Neha and Gatterbauer, Wolfgang},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,639 | Circuit Bounds for Conjunctive Queries with Self-joins | 2025 | PODS | 5.093636e-05 |
| 10,652 | Smallest Synthetic Witnesses for Conjunctive Queries | 2025 | PODS | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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