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Elicitation is a structured method of communication used to extract predetermined information from people without making them aware that they are a collection target. Elicitation comes in many forms. Communications can be verbal or written.
There are a few methods of knowledge acquisition in AI: 1. Expert systems: In this method, experts in a particular field provide rules and knowledge to a computer system, which can then be used to make decisions or solve problems in that domain.
Knowledge elicitation is a sub-process of knowledge acquisition (which deals with the acquisition or capture of knowledge from any source), and knowledge acquisition is, in turn, a sub-process of knowledge engineering (which is a discipline that has evolved to support the whole process of specifying, developing and
Eliciting (elicitation) is term which describes a range of techniques which enable the teacher to get learners to provide information rather than giving it to them.
In artificial intelligence, an expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as ifthen rules rather than through conventional procedural code.
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Knowledge elicitation is the process whereby a knowledge engineer works with a domain expert, such as an architect or engineer, to extract knowledge before codifying it into a machine-readable format. Needless to say, this is not a trivial process as knowledge can be both explicit and tacit.
Eliciting a probability distribution is the process of extracting an experts beliefs about some unknown quantity of interest, and representing his/her beliefs with a probability distribution.
Knowledge acquisition techniques including interviewing, observations, protocol analysis, discourse analysis, repertory grid analysis, brainstorming, Nominal Group Technique, Delphi technique, consensus decisionmaking, andcomputer-aided group sessions are then reviewed.

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