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R. Pichler, W. Fischl, G. Gottlob:
"General and Fractional Hypertree Decompositions: Hard and Easy Cases";
Talk: ACM SIGMOD/PODS International Conference on Management of Data, Houston, Texas, USA; 2018-06-10 - 2018-06-15; in: "Proceedings of the 37th {ACM} {SIGMOD-SIGACT-SIGAI} Symposium on Principles of Database Systems", ACM, (2018), ISBN: 978-1-4503-4706-8; 17 - 32.

Hypertree decompositions, as well as the more powerful generalized hypertree decompositions (GHDs), and the yet more general fractional hypertree decompositions (FHD) are hypergraph decomposition methods successfully used for answering conjunctive queries and for the solution of constraint satisfaction problems. Every hypergraph H has a width relative to each of these methods: its hypertree width hw(H), its generalized hypertree width ghw(H), and its fractional hypertree width fhw(H), respectively. It is known that hw(H) ≤ k can be checked in polynomial time for fixed k, while checking ghw(H) ≤ k is NP-complete for k >= 3. The complexity of checking fhw(H) ≤ k for a fixed k has been open for over a decade. We settle this open problem by showing that checking fhw(H) ≤ k is NP-complete, even for k=2. The same construction allows us to prove also the NP-completeness of checking ghw(H) ≤ k for k=2. After proving these results, we identify meaningful restrictions, for which checking for bounded ghw or fhw becomes tractable.

http://dx.doi.org/10.1145/3196959

Project Head Reinhard Pichler:
Effiziente, parametrisierte Algorithmen in Künstlicher Intelligenz und logischem Schließen

Project Head Reinhard Pichler:
HyperTrac