case-based reasoning


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case-based reasoning

An AI problem solving technique that catalogs experience into "cases" and matches the current problem to the experience. Such systems are easier to maintain than rule-based expert systems, because changes require adding new cases without the complexity of adding new rules. It is used in many areas including pattern recognition, diagnosis, troubleshooting and planning.
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The Case-Based Reasoning in Social Web Applications workshop was organized by Lara Quijano-Sanchez, from the Complutense University of Madrid, and Derek Bridge, from the University College Cork.
Several researchers and companies have tried out case-based reasoning methods for oil drilling assistance.
Her research focuses on intelligent learning systems in biology and medicine, with a particular emphasis on case-based reasoning and data mining as well as on biomedical applications of artificial intelligence.
We begin with an overview of transfer learning, case-based reasoning, and the three approaches for applying CBR to transfer learning.
The analysis of case-based reasoning research themes presented in Greene et al.
The ARTEnterprise Product Family is an industry-proven software system that emulates human judgment by using rules and a patented case-based reasoning engine to automate the decision-making process.
Aha (Naval Research Lab, USA) kicked off the event, making attendees question how case-based reasoning is perceived by the outside world and the balance between theoretical foundations and applied research.
The case-based reasoning community suggests that it is to find a piece of knowledge, schema, or case most relevant to its conceptual meaning and to apply it to the current situation so that a new structure can be built that provides causal linkages between what has already occurred and what is likely to occur next; that is, it provides causal explanation and expectation (Kolodner 1993; Leake 1992; Ram 1993; Schank 1986; Schank, Kass, and Riesbeck 1994).
The second day featured four workshops on various CBR related topics: health sciences, textual case-based reasoning, computer gaming and simulation environments, and similarities--processes--workflows.
Case-based reasoning (CBR) is particularly applicable to this problem domain because it (1) supports rich and evolvable representation of experiences--problems, solutions, and feedback; (2) provides efficient and flexible ways to retrieve these experiences; and (3) applies analogical reasoning to solve novel problems.
Through proactive advice, case-based reasoning tools and monthly statistical deliverables Standish delivers custom research services for the cost of a general research service.
Alternatively, if there are sufficient historical data, empirical methods such as case-based reasoning (CBR) (Aamodt and Plaza 1994), decision tree induction (Quinlan 1993), or statistical techniques can be lead to accurate prediction.