Abstract
Case Based Reasoning (CBR) is a knowledge management approach that consists of the development of decision-support systems where problems are solved by analogy with similar problems solved in the past. In this way, the system supports users in finding solutions without starting from scratch. CBR has become a very important research topic in artificial intelligence, with the definition of methodologies and architectural patterns for supporting developers in the design and implementation of case-based systems. This paper presents one of these frameworks, namely CRePERIE, an on-going research project based on the integration between CBR paradigm and metadata approach to obtain domain-independent case structure and retrieval algorithm definition. The paper focuses on how the developed retrieval strategy can be profitably exploited for the CBR revision step too, according to a substitutional approach.
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