Case-Based Reasoning and Some Typical Applications

Case-Based Reasoning and Some Typical Applications

Durga Prasad Roy (National Institute of Technology, India) and Baisakhi Chakraborty (National Institute of Technology, India)
DOI: 10.4018/978-1-4666-9624-2.ch049
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Case-Based Reasoning (CBR) arose out of research into cognitive science, most prominently that of Roger Schank and his students at Yale University, during the period 1977–1993. CBR may be defined as a model of reasoning that incorporates problem solving, understanding, and learning, and integrates all of them with memory processes. It focuses on the human problem solving approach such as how people learn new skills and generates solutions about new situations based on their past experience. Similar mechanisms to humans who intelligently adapt their experience for learning, CBR replicates the processes by considering experiences as a set of old cases and problems to be solved as new cases. To arrive at the conclusions, it uses four types of processes, which are retrieve, reuse, revise, and retain. These processes involve some basic tasks such as clustering and classification of cases, case selection and generation, case indexing and learning, measuring case similarity, case retrieval and inference, reasoning, rule adaptation, and mining to generate the solutions. This chapter provides the basic idea of case-based reasoning and a few typical applications. The chapter, which is unique in character, will be useful to researchers in computer science, electrical engineering, system science, and information technology. Researchers and practitioners in industry and R&D laboratories working in such fields as system design, control, pattern recognition, data mining, vision, and machine intelligence will benefit.
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Background And Motivation

What is case-based reasoning? Basically: To solve a new problem by remembering a previous similar situation and by reusing information and knowledge of that situation. Let us illustrate this by looking at some typical problem solving situations which is described in A. Aamodt, E. Plaza (1994).

  • A physician - after having examined a particular patient in his office - gets a reminding to a Patient that he treated two weeks ago. Assuming that the reminding was caused by a similarity of important symptoms (and not the patient's hair-color, say), the physician uses the diagnosis and treatment of the previous patient to determine the disease and treatment for the patient in front of him.

  • A drilling engineer, who have experienced two dramatic blow out situations, is quickly reminded of one of these situations (or both) when the combination of critical measurements matches those of a blow out case. In particular, he may get a reminding to a mistake he made during a previous blow-out, and use this to avoid repeating the error once again.

  • A financial consultant working on a difficult credit decision task uses a reminding to a previous case, which involved a company in similar trouble as the current one, to recommend that the loan application should be refused.

The first CBR workshops were organized in 1988, 1989, and 1991 by the U.S. Defence Advanced Research Projects Agency (DARPA). Which is formally marked the birth of the discipline of case-based reasoning. In 1993, the first European workshop on case-based reasoning (EWCBR, 1993) was held in Kaiserslautern, Germany. That was a great success, and that attracted more than 120 delegates and over 80 papers. Since then, many international workshops and conferences on CBR have been held in different parts of the world.

Now a day some of the Organizations such as IBM, VISA International, Volkswagen, British Airways, and NASA have already made use of CBR in applications such as customer support, quality assurance, aircraft maintenance, process planning, and decision support, and many more applications.

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