Research On The Ontology-based Expert System Model

Expert systems use knowledge stored in knowledge base to get the problem solving methods. An expert system has two main components; the knowledge base contains knowledge with which the inference engine draws conclusions. At present, most knowledge base and inference engine of expert system is designed for special domain and systems, which makes it hard to share and reuse knowledge with other systems. Inferences and facts are difficult to be separated. The application of such knowledge base is restricted, causing a tremendous waste of resources. Ontology can be used to build knowledge base of expert system, by which ontology can provide better inference mechanism, and basic frameworks for interoperability and knowledge share between different systems.Expert systems and ontology were introduced in the paper. Ontology description language, inference and building methods were studied. Ontology based expert systems were built to solve problems existed in knowledge base and inference engine of expert systems, and methods of building knowledge and rule bases were discussed; A JESS-based realization of the model was proposed, and methods of translating Ontology knowledge and rules to CLIPS syntax normative were given. Feasibility of the model was validated by simple example in the end of the paper.Knowledge base was built by ontology knowledge representation method, and inference rules were written by SWRL. Relationships between knowledge were represented effectively, realizing the reuse and sharing between knowledge base of different expert systems. The model can be applied in different domains, and different ontology description language and SWRL language can be chosen according to your requirements.