Research On The Technique Of Description Logic-based Ontology Reasoning

Semantic Web provides a reliable network frame mode for the automatic processing of information, it becomes the key to solving the Web information clutter, which can not quickly and efficiently retrieve and maintain information, so it got a widespread attention and had become a hot research topic. Ontology defines a formal specification for the shared conceptual model, which implements the sharing and exchanging of Web information in ontology layer, and becomes the focus of the study of Semantic Web. However, how to quickly and efficiently implements retrieval, sharing and related processing of knowledge for an increasing number of different areas of the ontology has become a problem. Ontology reasoning is to extract the hidden knowledge from the explicitly definition and declaration, and facilitate the sharing and related processing of knowledge, which provides a guideline to solve the above problems. Description logic has a good mechanism of knowledge’s representation and reasoning, therefore, it is important to study ontology reasoning technology based on description logic.In this paper, algorithms and related technologies had been deeply studied, which were used in the process of ontology reasoning. Through the study of the existing literature, we found that the worst time complexity of Tableau algorithm used currently in the reasoning is NExp Time, and the efficiency of optimization technology is not obvious. Therefore, this paper takes reality into account, and proposes an optimized concept classification algorithm on the basis of Tableau algorithms, which can effectively improve the efficiency of ontology reasoning. Through the comparison of experiments, the feasibility of the optimized concept classification algorithm is validated.In this paper, an ontology reasoning system has been designed and implemented, which is based on the description logic, and the optimized concept classification algorithm is used in the ontology reasoning system to guide ontology reasoning services. The architecture of ontology reasoning system has be attributed to parsers, reasoning engines and query engines etc, then the relevant module of ontology reasoning systems is refined and implemented based on the architecture, which enables the integrated services of ontology reasoning system, such as reads, analyzes, reasoning, inquiries, feedbacks and so on. Then the interoperability of the ontology reasoning system has been enhanced by optimizing the user interface.