Case-Based Reasoning Tutorial
July, 2009, Leipzig/Germany
CBR solves problems using the already stored knowledge, and captures new knowledge, making it immediately available for solving the next problem. Therefore, case-based reasoning can be seen as a method for problem solving, and also as a method to capture new experience and make it immediately available for problem solving. It can be seen as a learning and knowledge-discovery approach, since it can capture from new experience some general knowledge, such as case classes, prototypes and some higher-level concept.
The idea of case-based reasoning originally came from the cognitive science community which discovered that people are rather reasoning on formerly successfully solved cases than on general rules. The case-based reasoning community aims to develop computer models that follow this cognitive process. For many application areas computer models have been successfully developed, which were based on CBR, such as signal/image processing and interpretation tasks, help-desk applications, medical applications and E-commerce product-selling systems.
In the tutorial we will explain the case-based reasoning process scheme. We will show what kind of methods are necessary to provide all the functions for such a computer model. We will develop the bridge between CBR and other disciplines. Examples will be given based on signal-interpreting applications and information management.
||Introduction to CBR
||CBR in Information Management/Signal Processing
||End of Tutorial
Andrea Ahlemeyer-Stubbe has been working internationally as an independent business consultant since 1999. Her service-offerings focus on Business Intelligence (BI), Database Marketing (DBM) and
Customer Relationship Management (CRM) .Professional services are extended customized to fit the individual needs of her clients and their projects. She draws on the wealth of experience gained from her 15 years in the industry specifically in the areas of Data Mining and Data Warehousing.
Her customers are national and international key players in their markets. The services offered may range from the outsourcing of Analytics and Data Mining by the company to an on-site Consulting and interim management and could end with an on-site and/or off-site coaching and training.
Isabelle Bichindaritz is an assistant professor at the University of Washington, Computing and Software Systems, in Tacoma, WA, USA since 2002, where she directs the Laboratory of Informatics and Artificial Intelligence. She holds a Ph.D. in Computer Science from Université René Descartes - Paris V (1994). Her research focuses on intelligent learning systems in biology and medicine, case-based reasoning, and data mining. She has co-organized five workshops on Case-based Reasoning in the Health Sciences and organized two workshops on Data Mining in the Life Sciences. She has published over 80 scientific papers, and has edited several journals special issues.
Petra Perner is the director of the Institute of Computer Vision and Applied Computer Sciences IBaI. Her research interest is image analysis and interpretation, machine learning, data mining, machine learning, image mining and case-based reasoning. Recently, she is working on various medical, chemical and biomedical applications, information management applications, technical diagnosis and e-commerce applications. She has published numerous scientific publications and patents and is often requested as a plenary speaker in distinct research fields as well as across disciplines. Her vision is to build intelligent flexible and robust data-interpreting systems that are inspired by the human case-based reasoning process.
Michael M. Richter received his Doctoral Degree in Mathematics in 1968 from the University of Freiburg, Germany. He was Professor of Mathematics at the RWTH Aachen from 1975 to 1986 and Professor of Computer Science at the University of Kaiserslautern from 1986 until his retirement in 2003. He was president of the German Association for Mathematical Logic from 1981 to 1985 and served as Scientific Director at the German Research Center for Artificial Intelligence from 1989 to 1993. Presently he is Adjunct Professor at the University of Calgary, Canada. His main scientific interests are presently Artificial Intelligence and Software Engineering.