文章基本信息

标题：A Methodological Approach to Model CBR-Based Systems
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作者：Eliseu M. Oliveira ; Rafael F. Reale ; Joberto S. B. Martins 等
期刊名称：Journal of Computer and Communications
印刷版ISSN：2327-5219
电子版ISSN：2327-5227
出版年度：2020
卷号：8
期号：9
页码：1-16
DOI：10.4236/jcc.2020.89001
出版社：Scientific Research Publishing
摘要：Artificial intelligence (AI) has been used in various areas to support system optimization and find solutions where the complexity makes it challenging to use algorithmic and heuristics. Case-based Reasoning (CBR) is an AI technique intensively exploited in domains like management, medicine, design, construction, retail and smart grid. CBR is a technique for problem-solving and captures new knowledge by using past experiences. One of the main CBR deployment challenges is the target system modeling process. This paper presents a straightforward methodological approach to model CBR-based applications using the concepts of abstract and concrete models. Splitting the modeling process with two models facilitates the allocation of expertise between the application domain and the CBR technology. The methodological approach intends to facilitate the CBR modeling process and to foster CBR use in various areas outside computer science.
关键词：Artificial Intelligence;Case-Based Reasoning;CBR Modeling;Bandwidth Allocation Model