Semantic Web Fuzzy Ontology Based Knowledge Reasoning Research

The next generation of the World Wide Web is the Semantic Web, in that the processing of information is more easily to understand by the machine. However, with the development of networks, a large number of uncertain fuzzy vague information needs to be expressed and reasoning. In Semantic Web, knowledge structure is represented in the form of ontology, and the knowledge reasoning of fuzzy ontology is an important part in the application of Semantic Web, therefore a capable of handling fuzzy information ontology inference engine will be required. In this paper, there are some results by studying the existing ontology languages and reasoning mechanism.Firstly, the existing ontology reasoner is unilaterally based on description logic or rules respectively, which has its limitation in dealing with fuzzy ontology. Because of the differentiation of fuzzy ontology representation methods between all reasoners, the low processing efficiency is consequentially made.Secondly, in order to solve the bottleneck problem of fuzzy ontology knowledge reasoning, taking fuzzy ontology as application object, the problems about fuzzy ontology, fuzzy ontology representation method and fuzzy description logic are emphatically investigated, and the comparative analysis of existing fuzzy ontology reasoners is carried out. In this paper, comparing the advantages and disadvantages of several reasoners in detail, Jena rules engine is proposed, that is used to parse fuzzy ontology in the specific domain. At the same time because the Jena can write the user defined rules, to make up for the lack of built-in reasoning rules. Then Pellet based on description logic reasoner is selected to check whether fuzzy ontology is in contradiction to the fuzzy knowledge, to ensure the consistency of the fuzzy ontology knowledge in semantic web. Use FuzzyDL that only support fuzzy data type information to implement fuzzy ontology knowledge reasoning of the Semantic Web.Lastly, by virtue of the advantages of the Pellet, Jena and FuzzyDL, the mixed methods of rule and description logic reasoning combination is introduced, and a novel hybrid fuzzy ontology reasoner framework is proposed to implement fuzzy ontology knowledge reasoning, By reducing of fuzzy ontology and checking of the consistency of fuzzy ontology, consequently the efficiency and accuracy of the reasoning will be improved.