Abstract
Case-based reasoning (CBR) is a problem solving methodology that focuses on reusing lessons obtained from previous (possibly generalized) experiences towards solving new problems (Kolodner, 1993; Aamodt & Plaza, 1994; Watson, 1999; Bergmann, 2002). Originally conceived by cognitive scientists, since 1993 the CBR community has focused primarily on issues of interest to artificial intelligence researchers and practitioners. Some research topics of particular interest include case representation and indexing, solution retrieval and adaptation, learning (e.g., case acquisition), and integrating case-based approaches with others. Some motivating applications have included those related to customer support, recommender systems, knowledge management, diagnosis, the health sciences, and legal reasoning.
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Aha, D.W. (2005). Conversational Case-Based Reasoning. In: Pal, S.K., Bandyopadhyay, S., Biswas, S. (eds) Pattern Recognition and Machine Intelligence. PReMI 2005. Lecture Notes in Computer Science, vol 3776. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590316_4
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DOI: https://doi.org/10.1007/11590316_4
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