Successful Case-based Reasoning Applications

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.

Auteur

Stefania Montani (PhD in Bioengineering and Medical Informatics 2001, University of Pavia, Italy) is an Assistant Professor in Computer Science, at the Computer Science Department of the University of Piemonte Orientale, Alessandria, Italy. Her research interests include Case-Based Reasoning, Decision Support Systems, Temporal Databases, Temporal Reasoning, and Dependability Analysis. She is author of more than 100 publications, all in international journals, books, or international refereed conferences. She is member of more than 10 program committees of international conferences in 2009/2010, and belongs to the reviewing boards of 3 international journals. In 2010 she will be the program chair of the International Conference on Case-Based Reasoning, further testifying her very active role in the Case-Based Reasoning research community. Professor Lakhmi C. Jain is a Director/Founder of the Knowledge-Based Intelligent Engineering Systems (KES) Centre, located in the University of South Australia. He is a fellow of the Institution of Engineers Australia. His interests focus on the artificial intelligence paradigms and their applications in complex systems, art-science fusion, virtual systems, e-education, e-healthcare, unmanned air vehicles and intelligent agents.

Texte du rabat

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.

Contenu

Innovations in Case-Based Reasoning Applications.- Case-Based Reasoning for Medical and Industrial Decision Support Systems.- Development of Industrial Knowledge Management Applications with Case-Based Reasoning.- Case Based Reasoning for Supporting Strategy 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.- CookIIS - A Successful Recipe Advisor and Menu Creator.