Semantic decision making using ontology-based soft sets

Abstract

Molodtsov initiated the concept of soft set theory, which can be used as a generic mathematical tool for dealing with uncertainty. Description Logics (DLs) are a family of knowledge representation languages which can be used to represent the terminological knowledge of an application domain in a structured and formally well-understood way. To extend the expressive power of soft sets, ontology-based soft sets are presented by using the concepts of DLs to act as the parameters of soft sets. In this paper, we investigate soft set based decision making problems more deeply. Concretely, we first point out that the traditional approaches to (fuzzy) soft set based decision making are not fit to solve decision making problems involving user queries through some motivating examples. Furthermore, we present a novel approach to semantic decision making by using ontology-based soft sets and ontology (i.e., DL) reasoning. Lastly, the implementation method of semantic decision making is also discussed.