An Executive Model to Improve Reasoning and Realization in Ontology using Fuzzy-Colored Petri Nets

Despite the success of ontology in knowledge representation, its reasoning is still challenging. The main challenge in the reasoning of the ontology-based methods is to improve the reasoning process realization. The time complexity of the realization problem-solving process is equal to that of NEXP Time. This can be achieved by solving the subsumption and satisfiability problems. In addition, uncertainty and ambiguity are inevitable in these characteristics. Considering these requirements, using fuzzy theory is necessary. A method is proposed in this work in order to overcome this problem, which provides a new solution with a suitable time position. This work aims to model and improve the reasoning and realization in an ontology using Fuzzy-Colored Petri Nets (FCPNs). To this end, an algorithm for improving the realization problem is presented. Then, the Unified Modeling Language (UML) class diagram is used for standard description and representation of the efficiency characteristics. The Resource Description Framework Schema (RDFS) representation is converted to the UML diagram. Then, the fuzzy concepts are introduced in FCPNs. Then, an algorithm for converting the ontology description based on the UML class diagram into an executive model based on FCPNs is presented. Using this approach, a simple method is developed in order to obtain the desired results from an executive model and reasoning based on FCPNs through various queries. Finally, the efficiency of the proposed method is evaluated. The results obtained show that the performance of the proposed method is improved from various aspects.