Oliveira, E.M., Reale, R.F. and Martins, J.S.B. (2017) Evaluating CBR Similarity Functions for BAM Switching in Networks with Dynamic Traffic Profile. Proceedings of the V International Workshop on Advances in ICT Infrastructure and Services, Paris, January 2017, 1-7.

has been cited by the following article:

• TITLE: A Methodological Approach to Model CBR-Based Systems

  AUTHORS: Eliseu M. Oliveira, Rafael F. Reale, Joberto S. B. Martins

  KEYWORDS: Artificial Intelligence, Case-Based Reasoning, CBR Modeling, Bandwidth Allocation Model

  JOURNAL NAME: Journal of Computer and Communications, Vol.8 No.9, September 4, 2020

  ABSTRACT: 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.