FPT Parameterisations of Fractional and Generalised Hypertree Width
Summary: First exact FPT algorithms for generalized and fractional hypertree width, parameterized by target width, rank, and maximum degree. A new elimination-forest normal form extends MSO-transduction optimization to manageable width functions, also covering discretized adaptive width. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Matthias Lanzinger (Vienna University of Technology)
- 2. Igor Razgon (Durham University)
- 3. Daniel Unterberger (Vienna University of Technology)
BibTeX Citation
@inproceedings{lanzinger_pods26,
address = {New York, NY, USA},
series = {{PODS} '26},
title = {{FPT Parameterisations of Fractional and Generalised Hypertree Width}},
url = {https://dl.acm.org/doi/10.1145/3801900},
doi = {10.1145/3801900},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Lanzinger, Matthias and Razgon, Igor and Unterberger, Daniel},
year = {2026}
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 321 | Worst-Case Optimal Join Algorithms: Techniques, Results, and Open Problems | 2018 | PODS | 0.00021283186 |
| 673 | Generalized Hypertree Decompositions: NP-Hardness and Tractable Variants | 2007 | PODS | 0.00015095061 |
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