Ebook: Successful Case-based Reasoning Applications - I

Case-based reasoning offers tremendous advantages over other AI based techniques in all those fields where experiential knowledge is readily available. This research book presents a sample of successful applications of case-based reasoning. The contributions include: • Introduction to case-based reasoning • Case-based reasoning for medical and industrial support systems • Industrial knowledge management applications • Decision making in small and medium enterprises • Heterogeneity in ontological CBR systems • The adaptation problem in medical case-based reasoning systems • Prototype-based classification in unbalanced biomedical problems • Case-based ranking for environmental risk assessment • Recipe advisor and menu creator The book is directed to the application engineers, scientists, professors and students who wish to develop successful case-based reasoning applications.

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Case-based reasoning (CBR) is an Artificial Intelligence (AI) technique to support the capability of reasoning and learning in advanced decision support systems. CBR exploits the specific knowledge collected on previously encountered and solved situations, which are known as cases. In this book, we have collected a selection of papers on very recent CBR applications. These, after an in-depth analysis of their specific application domain needs, propose proper methodological solutions and give encouraging evaluation results, which have in some cases led to the commercialization step. The collected contributions demonstrate the capability of CBR to solve or handle issues which would be too difficult to manage with other classical AI methods and techniques, such as rules or models. The heterogeneity of the involved application domains indicates the flexibility of CBR, and its applicability in all those fields where experiential knowledge is (readily) available.