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Combining cases and rules to provide contextualised knowledge based systems

机译:结合案例和规则来提供基于语境化的知识系统

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Providing contextualised knowledge often involves the difficult and time-consuming task of specifying the appropriate contexts in which the knowledge applies. This paper describes the Ripple Down Rules (RDR) knowledge acquisition and representation technique which does not attempt to define up front the possible context/s. Instead cases and the exception structure provide the context and rules provide the index by which to retrieve the case/s. KA is incremental. The domain expert locally patches rules as new cases are seen. Thus RDR is a hybrid case-based and rule-based approach. The use of Formal Concept Analysis to translate the RDR performance system into a formal context and uncover an explanation system in the form of an abstraction hierarchy further strengthens our emphasis on the combined use of cases and rules to provide contextualised knowledge.
机译:提供上下文化的知识往往涉及指定知识所适用的适当环境的困难和耗时的任务。本文介绍了不尝试定义可能的上下文/ s的纹波下规则(RDR)知识获取和表示技术。而是案例和异常结构提供上下文和规则提供了检索案例/ s的索引。 ka是渐进的。域专家当地修补规则作为新案例。因此RDR是一种基于混合案例和基于规则的方法。使用正式概念分析将RDR性能系统转化为正式的上下文,并以抽象层次结构的形式揭示了解释系统,进一步加强了我们对案件和规则的联合使用,以提供内容化知识的强调。

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