Research On Database-based OWL Ontology Fuzzy Query Method

The Semantic Web was proposed by Tim Berners-Lee who invented Web in1998, and it would be an extension of today’s web. Information in the Semantic Web has well-dfined meaning, so computers could understand the messages, consequently the cooperation between people and computers would become very well.In recent years, the ontology, which enables a shared, formal, explicit and common description of domain knowledge, has been recognized to play an important role in the Semantic Web. With the increasing use of the ontology in the Semantic Web, it is critical to supply an efficient method to query the information in the ontology.Especially fuzzy query, which is closer to the nature language, has been paid more and more attention to recently.Currently, the ontology fuzzy query roughly divided into two categories:First, the fuzzy data are stored directly in the ontology files; Second, the fuzzy extension of the existent ontology query language. Fuzzy information in the form of expression in the real world is very complex, it is difficult to unified model for storage, and the update will also become more complex, so the storage of fuzzy ontology has limitations. Fuzzy extension of the ontology query language, dependent on the carrier of the storage. Relational database has been widely used in various fields, so, taking the relational database as the carrier of the ontology storage is the best choice. The next issues to consider are:how to ensure the integrity of the ontology data stored in the database, and how to express the users’ fuzzy queries intentions, and how to deal with fuzzy queries. Based on these three issues and study on the present research and technology of the ontology fuzzy query, this paper presents a method of relational database based OWL Ontology fuzzy Query.The main content of the method proposed by this paper is:first, proposed a storage mode of OWL ontology based on relational database. On the basis of the database schema, a description logic reasoner is used to extract the implicit information. Secondly, the core content of this paper, defines a fuzzy query language with a threshold and a weight, and proposed a method on how to deal with the fuzzy query. The main idea of the algorithm is to translate the fuzzy query conditions entered by users into the accurate SQL query, using the fuzzy set theory. Finally, to verify the proposed method, this paper designs a prototype system. Experiments show that the proposed method is feasible. Through the analysis of experimental results, the system has a lower query response time and higher recall rate.