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Non-Standard Inferences in Description Logics [electronic resource] /

Contributor(s): Küsters, Ralf [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computer Science: 2100Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2001.Description: X, 254 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540446132.Subject(s): Computer science | Software engineering | Mathematical logic | Artificial intelligence | Computer Science | Artificial Intelligence (incl. Robotics) | Software Engineering/Programming and Operating Systems | Mathematical Logic and Formal LanguagesOnline resources: Click here to access online
Contents:
Description Logics -- Non-Standard Inferences -- Characterizing Subsumption -- LCS and MSC -- Matching -- Conclusion.
In: Springer eBooksSummary: Description logics (DLs) are used to represent structured knowledge. Inference services testing consistency of knowledge bases and computing subconcept/superconcept hierarchies are the main feature of DL systems. Intensive research during the last fifteen years has led to highly optimized systems that allow to reason about knowledge bases efficiently. However, applications often require additional non-standard inferences to support both the construction and the maintenance of knowledge bases, thus making the inference procedures again incomplete. This book, which is a revised version of the author's PhD thesis, constitutes a significant step to fill this gap by providing an excellent formal foundation of the most prominent non-standard inferences. The descriptions given include precise definitions, complete algorithms and thorough complexity analysis. With its solid foundation, the book also serves as a basis for future research.
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Description Logics -- Non-Standard Inferences -- Characterizing Subsumption -- LCS and MSC -- Matching -- Conclusion.

Description logics (DLs) are used to represent structured knowledge. Inference services testing consistency of knowledge bases and computing subconcept/superconcept hierarchies are the main feature of DL systems. Intensive research during the last fifteen years has led to highly optimized systems that allow to reason about knowledge bases efficiently. However, applications often require additional non-standard inferences to support both the construction and the maintenance of knowledge bases, thus making the inference procedures again incomplete. This book, which is a revised version of the author's PhD thesis, constitutes a significant step to fill this gap by providing an excellent formal foundation of the most prominent non-standard inferences. The descriptions given include precise definitions, complete algorithms and thorough complexity analysis. With its solid foundation, the book also serves as a basis for future research.

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