Optimal compression of propositional Horn knowledge bases: complexity and approximation
Artificial Intelligence
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Theoretical Computer Science
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Theory of Relational Databases
Theory of Relational Databases
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ICFCA '09 Proceedings of the 7th International Conference on Formal Concept Analysis
Contextual attribute logic of many-valued attributes
Formal Concept Analysis
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Discrete Applied Mathematics
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A well-known result is that the inference problem for propositional Horn formulae can be solved in linear time. We show that this remains true even in the presence of arbitrary (static) propositional background knowledge. Our main tool is the notion of a cumulated clause, a slight generalization of the usual clauses in Propositional Logic. We show that each propositional theory has a canonical irredundant base of cumulated clauses, and present an algorithm to compute this base.