The Application Research Of Knowledge Base System On The Basis Of Ontology

In the 1990s, ontology became a hot topic of artificial intelligence research areas. Ontology is defined as a clear formal specification which sharing conceptual model. Ontology includes concepts, relations, examples, rules and methods. According to the definition of ontology, there are many kinds of formal model in the field of knowledge engineering that can be used to represent ontology. In recent years, description logic receives people's particular concern, the main reasons includes: it has a clear semantic of model, it is appropriate to represent application areas through concept classification, and also provides a reasoning service that can be judged.The classical description logic can only define the definite concepts and attributes, and it can only return definite results from this definite reasoning, obviously is unable to solve fuzzy question of the ontology system in the real world. Straccia extended description logic ALC (Attributive Concept Description Language with Complements) to fuzzy description logic FALC (Fuzzy ALC), this logic combines the characters of fuzzy logic and description logic. The fuzzy description logic as a formal basis of the knowledge representation, has a strong knowledge representation and reasoning ability, but can't deal with non-monotonic, incomplete knowledge.Based on the above, this article expands fuzzy description logic FALC, which add default rules and constraint set.It puts forward a kind of new description logic—non-monotonic fuzzy description logic NFALC (Non-monotonic FALC), which not only can deal with non-monotonic, incomplete knowledge but also can deal with fuzzy knowledge. This article presents NFALC syntax and semantic explain, studys the properties of NFALC, gives the corresponding relationships between NFALC and OWL, at the same time gives the reasoning algorithm base on NFALC—Tableaux-N algorithm.This article builds knowledge base model based on ontology and gives ontology-based query system architecture, and then applys this knowledge base system on Intelligent Tutoring System.