Soft and Constrained Hypertree Width
Summary: Proposes soft hypertree width (shw), a relaxation of hypertree width for CQ evaluation via candidate decompositions. Shw never exceeds hw and can be smaller, preserving tractability while enabling constraints and preferences; prototype experiments show practical impact. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Matthias Lanzinger
- 2. Cem Okulmus
- 3. Reinhard Pichler
- 4. Alexander Selzer
- 5. Georg Gottlob
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Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 623 | Generalized Hypertree Decompositions: NP-Hardness and Tractable Variants | 2007 | PODS | 0.00018976192 |
| 3,236 | TPC-DS, Taking Decision Support Benchmarking to the Next Level | 2002 | SIGMOD | 7.3294564e-05 |
| 3,516 | Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs | 2022 | VLDB | 7.018912e-05 |
| 4,466 | Robust Join Processing with Diamond Hardened Joins | 2024 | VLDB | 6.1545841e-05 |
| 5,076 | HyperBench: A Benchmark and Tool for Hypergraphs and Empirical Findings | 2019 | PODS | 5.709895e-05 |
| 7,500 | Ranked Enumeration of Minimal Triangulations | 2019 | PODS | 4.7135369e-05 |
| 8,485 | Fast Parallel Hypertree Decompositions in Logarithmic Recursion Depth | 2022 | PODS | 4.4956257e-05 |
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