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Knowledge representation and reasoning

Knowledge representation (KR) aims to model information in a structured manner to formally represent it as knowledge in knowledge-based systems whereas knowledge representation and reasoning (KRR, KR&R, or KR²) also aims to understand, reason, and interpret knowledge. KRR is widely used in the field of artificial intelligence (AI) with the goal of…

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Knowledge extraction

Ontology engineering

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Knowledge representation and reasoning

Nodes123
Edges122
Triples120
Avg. degree1.98
Density0.01626
Components1

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Knowledge representation and reasoning

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related to Further reading · 74
Knowledge representation and reasoning → Addison-Wesley, AI Magazine, An Analysis, Anne Williams, Arthur, Associates, Belief Revision, Berlin, Brachman, Brooks/Cole, Bruce Porter, Computational Foundations, Conceptual Graphs, Didier Roland, ER, Fagin, Frontiers, Graph-based Knowledge Representation, Halpern, Handbook
related to External links · 19
Knowledge representation and reasoning → Archived, Bolzano, CLASSIC ApplicationThe Rule Markup, Computer Science, Description Logics, Enrico Franconi, Faculty, Free University, InitiativeNelements KOS, ItalyDATR Lexical, Knowledge Modeling, Knowledge Representation, PagePrinciples, Pejman MakhfiIntroduction, Practice, Randall Davis, Reasoning Incorporated Description Logic, Wayback MachineLoom Project Home, What

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knowledge representation logic systems reasoning language also rules languages frame world semantic information one used ai fol ontology formalisms rather

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
convolutional neural networksinstance ofincluding neural network architectures0.80text
transformersinstance ofincluding neural network architectures0.80text
the General Problem Solverinstance ofThe earliest work in computerized knowledge representation was focused on general problem-solvers0.80text
Ed Feigenbauminstance ofAI researchers0.80text
Frederick Hayes-Roth advocated the representation of domain-specific knowledge rather than general-purpose reasoning.These efforts led to the cognitive revolution in psychologyinstance ofAI researchers0.80text
to the phase of AI focused on knowledge representation that resulted in expert systems in the 1970sinstance ofAI researchers0.80text
80sinstance ofAI researchers0.80text
production systemsinstance ofAI researchers0.80text
frame languagesinstance ofAI researchers0.80text
etcinstance ofAI researchers0.80text
ordering food in a restaurant narrow the search spaceinstance ofe.g. understanding natural language and the social settings in which various default expectations0.80text
allow the system to choose appropriate responses to dynamic situations.It was not long before the frame communitiesinstance ofe.g. understanding natural language and the social settings in which various default expectations0.80text

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