3 research outputs found
Adaptation Knowledge Discovery from a Case Base
In case-based reasoning, the adaptation step depends in general on
domain-dependent knowledge, which motivates studies on adaptation knowledge
acquisition (AKA). CABAMAKA is an AKA system based on principles of knowledge
discovery from databases. This system explores the variations within the case
base to elicit adaptation knowledge. It has been successfully tested in an
application of case-based decision support to breast cancer treatment
Case Base Mining for Adaptation Knowledge Acquisition
In case-based reasoning, the adaptation of a source case in order to solve
the target problem is at the same time crucial and difficult to implement. The
reason for this difficulty is that, in general, adaptation strongly depends on
domain-dependent knowledge. This fact motivates research on adaptation
knowledge acquisition (AKA). This paper presents an approach to AKA based on
the principles and techniques of knowledge discovery from databases and
data-mining. It is implemented in CABAMAKA, a system that explores the
variations within the case base to elicit adaptation knowledge. This system has
been successfully tested in an application of case-based reasoning to decision
support in the domain of breast cancer treatment
Adaptation Knowledge Discovery from a Case Base
In case-based reasoning, the adaptation step depends in general on domain-dependent knowledge, which motivates studies on adaptation knowledge acquisition (AKA). CABAMAKA is an AKA system based on principles of knowledge discovery from databases. This system explores the variations within the case base to elicit adaptation knowledge. It has been successfully tested in an application of case-based decision support to breast cancer treatment