Seminar on Computational Learning and
Adaptation
Maintenance of Diagnostic Case-Based Reasoning Systems
Ioannis Iglezakis
DaimlerChrysler AG
Research & Technology
RIC/AM - Information Mining
During the last decade, case-based reasoning has evolved from initial
ideas that originated in cognitive science to a well established
intelligent technology suitable for various applications. One
consequence is that the focus of current case-based reasoning
research has moved from basic issues - like representation, acquisition,
retrieval, and indexing - toward the maintenance of large-scale systems.
However most methods for maintenance only consider removing cases to
restoring prediction accuracy. As a consequence, knowledge is lost
and prediction accuracy is viewed as the only requirement useful for
satisfying customers. This talk considers ways to improve cases
besides removing them and applies a methodology for maintaining the
knowledge of diagnostic case-based reasoning systems. The methodology
indirectly measures and monitors customer requirements and restores
them if necessary.
Date: Thursday, November 21
|
Time: 4:15-5:30PM
|
Place: Cordura 100
|
Return to the seminar schedule