基于案例的推理:相似性度量的问题和重要性

I. Chourib, G. Guillard, M. Mestiri, B. Solaiman, I. Farah
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引用次数: 2

摘要

本文试图概述与基于案例推理相关的基本概念、结构和术语,因为我们的目标是研究基于案例推理过程的演变,使我们能够整合知识库,确保信息的一致性,整合推理模式:相似、分类和混合。此外,本文还讨论了相似度度量的概念和相关问题,相似度度量在医疗系统中非常重要,使用相似度度量可以降低患者健康错误的风险。然而,这似乎非常复杂,因为相似性的测量必须考虑到每个患者的信息类型(定性、文本、定量等)的多样性。最后,我们对(GS.52)中应用的相似性度量进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Case-Based Reasoning: Problems And Importance Of Similarity Measure
This article attempts to provide an overview of the basic concepts, structure and terms related to case-based reasoning, because we aim to work on an evolution of the CBR process which allows us to integrate the knowledge base, ensure the consistency of information, integrate the modes of reasoning: similarity, classification and hybrid. In addition, this article discusses the concept and issues related to similarity measure, which is very important in medical system and using it allows to reduce the risks of health error for patients. However, it seems very complex because the measure of similarity must take into account the diversity of the types of information (qualitative, textual, quantitative, etc.) for each patient. And at the end, we represent an evaluation of similarity measure which was applied in (GS.52).
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