Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation

Abstract

Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer:1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, delete-cascade, logical inconsistency and dead choice detection.