Research On Fuzzy Description Logic F-SHIQ Axiom System And Reasoning Mechanism

With the rapid development of computer and Internet, semantic web and description logic become more and more important in artificial intelligence and other fields, and the knowledge acquisition and knowledge reasoning based on semantic web has also increased. However, in our daily life, more and more uncertain and incomplete information needed to be resolved, so this requires a complete system with theory and practice to deal with the vague knowledge, including the representation and reasoning of fuzzy information. In this paper, we make the fuzzy logic as the basis theory, learn existing theories and technology based on the Semantic Web, and focus on the improvement of the theoretical and practical applicability of the two key issues. The main research results are as follows:(1)An Fuzzy Description Logic Axiom System named F-SHIQ is proposed as basic theroty for knowledge representation and reasoning. And a fuzzy extension of necessary concept, relations and operation of description logic is given in the point of axiom system construction. This axiom system gives corresponding definitions, rules, axioms, theorems and reasoning proofs of theorems for the dependability.(2)A fuzzy SHIQ rule language FSRL based on F-SHIQ axiom system is proposed to extend existing ontology language OWL DL. The extension makes the knowledge expression language having the capability of fuzzy information representation and reasoning in the classes, properties, individuasl, and operations. And FSRL provides the necessary forms basis of knowledge expressions for the fuzzy reasoning behind. The knowledge and rules in reasoner are saved for reasoning application by FSRL.(3)A storage model using ontology and semantic rules is proposed to save the algorithms and theorems of fuzzy axiom system. The model broke down axiom system into simple concepts and relations, use the ontology as a Knowledge DataBase to save and build link to them via semantic rules. In this way, an efficient storage of the algorithms and theorems is realized to eliminate the redundancy.(4)Using F-SHIQ as the logic basis and FSRL for the knowledge expression and storage form, a fuzzy engine FSRLReasoner is given to reasoning fuzzy knowledge. For the fuzzy issue of Knowledge Base form, the reasoner parses it and then does fuzzy reasoning by the rules, gives the corresponding results. Finally, an experiment of KB reasoning is applied to prove the capacity of this reasoner.The research introduces the fuzzy logic to represent and reason knowledge in semantic web, and enhance the ability of dealing with fuzzy information. It also provides a set of fuzzy information processing system, and has a well theoretical and practical significance to the various field in the future fuzzy knowledge dealing.