Foundations of Management | 2010
Authors:
DOI: 10.2478/v10238-012-0021-z
Journal: Foundations of Management
Year: 2010
Publisher:
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
The purpose of this article is to present and analyse issues connected with the expert knowledge collection methodology in the decision support systems (DSS). The considerations concentrate on a conception of building an information system, based on an application of case-based reasoning method and reasoning based on approximate knowledge. The expert's knowledge is systematically collected in a case base. A mechanism of classical CBR and a logic model of the case base were described. It was assumed that the cases compared with regard to similarity are elements of tolerance space what considerably accelerates the retrieval of satisfying solutions. A local and global measure of case similarity is developed. The method can be used in complex tasks of image identification. © 2010, Versita. All rights reserved.
approximate knowledge; case; case base; case-based reasoning (CBR); CBR cycle; CBR mechanism; expert inference; Expert system; matrix of similarity; object-attribute-value; similarity of phenomena; tolerance space