Abstract
The existing ontology reasoners are all unilaterally description logic-based or rule-based, and their abilities to deal with fuzzy ontology are limited. It is the diversity of fuzzy ontology representation methods among them that leads to a low processing efficiency of fuzzy ontology. To solve this bottle-neck problem of fuzzy ontology-based knowledge reasoning, fuzzy ontology, fuzzy ontology representation method and fuzzy description logic are investigated, and the existing fuzzy ontology reasoners are comparatively analyzed. By virtue of the advantages of the typical reasoners such as Pellet, JenaAPI and fuzzyDL (fuzzy Description Logic), a method combining rule and description logic reasoning is designed, and a framework about fuzzy ontology based knowledge reasoning is proposed. By reducing fuzzy ontology, checking consistency and repairing inconsistency, the efficiency and accuracy of fuzzy ontology based knowledge reasoning can be improved. Finally, an experiment is given to verify the validity of proposed method.
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