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引用次数: 0

摘要

非编程专家只能在有限程度上对基于知识的系统进行交互式调整。作者提出了一种方法,为这类用户提供了额外的适应性层。新增的功能允许用户构建和指定新领域术语的语义,这些术语可以指领域实体、特征或关系。该方法依赖于领域语言术语的强类型和广泛索引。基于这种方法构建的系统显示了领域专家和知识库系统程序员之间的明确分工:领域专家添加描述特定领域元素的术语,而程序员为新术语的语义提供构建块。所提出的方法已经在一个名为KRAM.>的系统中作为机器学习项目的一部分实现
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Interactive extension of domain datatypes
Knowledge-based systems can be adapted interactively by non-programming experts to only a limited degree. The authors present an approach that delivers an additional layer of adaptability to such users. The added functionality allows the user to construct and specify the semantics of new domain terms, where these terms may refer to domain entities, characteristics or relations. The approach depends on strong-typing and extensive indexing of domain language terms. A system built on this approach exhibits a clear division of labor between the domain expert and a knowledge-base system programmer: the domain expert adds terms that describes particular domain elements while the programmer provides building blocks for a new term's semantics. The proposed approach has been implemented as part of a machine learning project in a system called KRAM.<>
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