Abstract
A basic feature of Terminological Knowledge Representation Systems is to represent knowledge by means of taxonomies, here called terminologies, and to provide a specialized reasoning engine to do inferences on these structures. The taxonomy is built through a representation language called a concept language (or description logic), which is given a well-defined set-theoretic semantics. The efficiency of reasoning has often been advocated as a primary motivation for the use of such systems. The main contributions of the paper are: (1) a complexity analysis of concept satisfiability and subsumption for a wide class of concept languages; (2) algorithms for these inferences that comply with the worst-case complexity of the reasoning task they perform. © 1997 Academic Press.
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CITATION STYLE
Donini, F. M., Lenzerini, M., Nardi, D., & Nutt, W. (1997). The Complexity of Concept Languages. Information and Computation, 134(1), 1–58. https://doi.org/10.1006/inco.1997.2625
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