Non-Standard Inferences in Description Logics [electronic resource] /
edited by Ralf Küsters.
- Berlin, Heidelberg : Springer Berlin Heidelberg, 2001.
- X, 254 p. online resource.
- Lecture Notes in Computer Science, 2100 0302-9743 ; .
- Lecture Notes in Computer Science, 2100 .
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.
9783540446132
10.1007/3-540-44613-3 doi
Computer science.
Artificial intelligence.
Computer Science.
Artificial Intelligence (incl. Robotics).
Mathematical Logic and Formal Languages.
Q334-342 TJ210.2-211.495
006.3
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.
9783540446132
10.1007/3-540-44613-3 doi
Computer science.
Artificial intelligence.
Computer Science.
Artificial Intelligence (incl. Robotics).
Mathematical Logic and Formal Languages.
Q334-342 TJ210.2-211.495
006.3