Improving rule-based systems through case-based reasoning
Improving rule-based systems through case-based reasoning
复制标题
通过基于案例的推理改进基于规则的系统
DOI：
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发表时间：
1991
期刊：
影响因子：
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通讯作者：
Andrew R. Golding
中科院分区：
文献类型：
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作者：
Andrew R. Golding
提出了一种结合规则推理和案例推理的新体系结构。其中心思想是将规则应用于目标问题，以获得答案的第一近似值;但如果该问题被判断为在其行为的任何方面都与规则的已知例外非常相似，那么该方面将以例外而不是规则为模型。该架构是为姓氏发音的全面任务而实现的。初步结果表明，该系统的性能几乎与最好的商业系统一样好。然而，比系统的绝对性能更令人感兴趣的是，这种性能比单独使用规则所能实现的性能更好。这说明了该体系结构改进其开始时基于规则的系统的能力。结果还表明，在系统中的一个有益的互动，在改进的规则加快了基于案例的组件。
A novel architecture is presented for combining rule-based and case-based reasoning. The central idea is to apply the rules to a target problem to get a first approximation to the answer; but if the problem is judged to be compellingly similar to a known exception of the rules in any aspect of its behavior, then that aspect is modelled after the exception rather than the rules. The architecture is implemented for the full-scale task of pronouncing surnames. Preliminary results suggest that the system performs almost as well as the best commercial systems. However, of more interest than the absolute performance of the system is the result that this performance was better than what could have been achieved with the rules alone. This illustrates the capacity of the architecture to improve on the rule-based system it starts with. The results also demonstrate a beneficial interaction in the system, in that improving the rules speeds up the case-based component.