Machine-readable Knowledge Bases
Machine-readable knowledge bases store knowledge in a computer-readable form, usually for the purpose of having automated deductive reasoning applied to them. They contain a set of data, often in the form of rules that describe the knowledge in a logically consistent manner. An ontology can define the structure of stored data - what types of entities are recorded and what their relationships are. Logical operators, such as And (conjunction), Or (disjunction), material implication and negation may be used to build it up from simpler pieces of information. Consequently, classical deduction can be used to reason about the knowledge in the knowledge base. Some machine-readable knowledge bases are used with artificial intelligence, for example as part of an expert system that focuses on a domain like prescription drugs or customs law. Such knowledge bases are also used by the semantic web.
See also List of artificial intelligence projects.
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Famous quotes containing the words knowledge and/or bases:
“There’s a theory, one I find persuasive, that the quest for knowledge is, at bottom, the search for the answer to the question: “Where was I before I was born.” In the beginning was ... what? Perhaps, in the beginning, there was a curious room, a room like this one, crammed with wonders; and now the room and all it contains are forbidden you, although it was made just for you, had been prepared for you since time began, and you will spend all your life trying to remember it.”
—Angela Carter (1940–1992)
“The information links are like nerves that pervade and help to animate the human organism. The sensors and monitors are analogous to the human senses that put us in touch with the world. Data bases correspond to memory; the information processors perform the function of human reasoning and comprehension. Once the postmodern infrastructure is reasonably integrated, it will greatly exceed human intelligence in reach, acuity, capacity, and precision.”
—Albert Borgman, U.S. educator, author. Crossing the Postmodern Divide, ch. 4, University of Chicago Press (1992)