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      KCI등재

      전문가(專門家)시스템 개발(開發)을 위한 지식획득(知識獲得)의 방법론(方法論) = THE KNOWLEDGE ACQUISITION METHDOLOGY FOR EXPERT SYSTEM DEVELOPMENT

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      https://www.riss.kr/link?id=A105598700

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      다국어 초록 (Multilingual Abstract)

      Knowledge acquisition is the process of gathering knowledge about a domain, usually from ex-pert, and transforming it to be executed in a program. It is a part of the knowledge-engineering process, which includes defining a problem, designing an architecture, building an knowledge base, and testing and refining the program. Knowledge acquisition is the bottleneck in this process.
      Knowledge acquisition methodologies are divided into three categories: knowledge driven, expert-drieven, and machine-driven. To evaluate knowledge acquisition methodologies, a framework is proposed by addressing the nature of knowledge and problem domains. Different methodologies in each category are described and evaluated for their ability to support various kinds of problem domain and type of knowledge they are designed to elicit.
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      Knowledge acquisition is the process of gathering knowledge about a domain, usually from ex-pert, and transforming it to be executed in a program. It is a part of the knowledge-engineering process, which includes defining a problem, designing an archi...

      Knowledge acquisition is the process of gathering knowledge about a domain, usually from ex-pert, and transforming it to be executed in a program. It is a part of the knowledge-engineering process, which includes defining a problem, designing an architecture, building an knowledge base, and testing and refining the program. Knowledge acquisition is the bottleneck in this process.
      Knowledge acquisition methodologies are divided into three categories: knowledge driven, expert-drieven, and machine-driven. To evaluate knowledge acquisition methodologies, a framework is proposed by addressing the nature of knowledge and problem domains. Different methodologies in each category are described and evaluated for their ability to support various kinds of problem domain and type of knowledge they are designed to elicit.

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