Knowledge Representation and Ontologies

• Published in: Scientific Data Mining and Knowledge Discovery pp. 111 - 137
• Main Author: Grimm, Stephan
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2010
• Subjects: Description Logic; Knowledge Representation; Logic Program; Logic Programming; Semantic Network
• ISBN: 3642027873; 9783642027871
• DOI: 10.1007/978-3-642-02788-8_6

Knowledge representation and reasoning aims at designing computer systems that reason about a machine-interpretable representation of the world. Knowledge-based systems have a computational model of some domain of interest in which symbols serve as surrogates for real world domain artefacts, such as physical objects, events, relationships, etc. [1]. The domain of interest can cover any part of the real world or any hypothetical system about which one desires to represent knowledge for com–putational purposes. A knowledge-based system maintains a knowledge base, which stores the symbols of the computational model in the form of statements about the domain, and it performs reasoning by manipulating these symbols. Applications can base their decisions on answers to domain-relevant questions posed to a knowledge base.