Structure identification in relational data
Artificial Intelligence - Special volume on constraint-based reasoning
Learning Conjunctions of Horn Clauses
Machine Learning - Computational learning theory
Optimal compression of propositional Horn knowledge bases: complexity and approximation
Artificial Intelligence
The Inverse Satisfiability Problem
SIAM Journal on Computing
A unified framework for structure identification
Information Processing Letters
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
On Horn Envelopes and Hypergraph Transversals
ISAAC '93 Proceedings of the 4th International Symposium on Algorithms and Computation
The complexity of satisfiability problems
STOC '78 Proceedings of the tenth annual ACM symposium on Theory of computing
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We give a new algorithm for computing a prepositional Horn CNF formula given the set of its models. Its running time is O(|R|n(|R| + n)), where |R| is the number of models and n that of variables, and the computed CNF contains at most |R|n clauses. This algorithm also uses the well-known closure property of Horn relations in a new manner.