On Tractable Queries and Constraints
DEXA '99 Proceedings of the 10th International Conference on Database and Expert Systems Applications
Robbers, marshals, and guards: game theoretic and logical characterizations of hypertree width
Journal of Computer and System Sciences - Special issu on PODS 2001
Reducing Redundancy in the Hypertree Decomposition Scheme
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
Weighted hypertree decompositions and optimal query plans
Journal of Computer and System Sciences
Generalized hypertree decompositions: np-hardness and tractable variants
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
SOFSEM'05 Proceedings of the 31st international conference on Theory and Practice of Computer Science
Heuristic Methods for Hypertree Decomposition
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
A greedy algorithm for constructing a low-width generalized hypertree decomposition
Proceedings of the 13th International Conference on Database Theory
Balanced queries: divide and conquer
MFCS'10 Proceedings of the 35th international conference on Mathematical foundations of computer science
Tackling the partner units configuration problem
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Decomposing combinatorial auctions and set packing problems
Journal of the ACM (JACM)
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Hypertree decompositions of hypergraphs are a generalization of tree decompositions of graphs. The corresponding hypertree-width is a measure for the acyclicity and therefore an indicator for the tractability of the associated computation problem. Several NP-hard decision and computation problems are known to be tractable on instances whose structure is represented by hypergraphs of bounded hypertree-width. Roughly speaking, the smaller the hypertree-width, the faster the computation problem can be solved. In this paper, we present the new backtracking-based algorithm det-k-decomp for computing hypertree decompositions of small width. Our benchmark evaluations have shown that det-k-decomp significantly outperforms opt-k-decomp, the only exact hypertree decomposition algorithm so far. Even compared to the best heuristic algorithm, we obtained competitive results as long as the hypergraphs are sufficiently simple.