Research Of Schema Mapping Of Distributed Database Based On Ontology

Ontology is a branch of philosophy, it used to show the nature and organization of things. From the distributed database administrator'view, it needs to build a method that can accurately express sharing concepts in an interactive process- ontology. Ontology that uses a definite, formalization ways to show the relationship between the concepts, becomes medium that application process can interunderstand the concept semanitic. During the information age,the distributed database will possiblely rely on the conceptual model based on ontology to precisely define all sorts of different symbol meaning.Each sub-system of the distributed database usually stores in different physical range, and uses smaller computer operation system. Each sub-system has a complete copy files, also has its own special sub-database. These database may use different operating systems and database storage structure. The advantages of the storage ways of this database is decling the required data transmission cost. The weakness is the increasing inquired the time, so the primary problem of distributed database to solve is to choose what kind of algorithm to accelerate query time .As a new research method, ontology semantic mapping method has the function of refining research problems. So we can use similar ontology in the ontology semantic mapping method to query the spot of some relevant issues.The query issue of these spots can use ontology semantic mapping similarity algorithm to solve. Apply this search method to distributed database query problem. This paper only choose some relatively simple sub-database from the distributed database to elaborate the above problems.According to the distributed database query problem,this paper use ontology semantic mapping method to solve how to select the optimal path during the distributed database query, and how to improve the efficiency of a distributed heterogeneous database query.First, according to the existing GLUE similarity algorithm based on ontology semantic mapping, proposes an improved algorithm to improve the original algorithm similarity in different mapping function. Due to the GLUE similarity algorithm is expressed by probability formula,but the probability calculation method usually make similarity reduced.Therefore, this paper use the maximum likelihood function in mathematics to improve the application of probability formula, increase the similarity effectively. Second, due to the existing distributed database query optimization algorithm is based on connection or half connection. According to query method based on half connection,this paper use improved GLUE similarity algorithm to find several different sub-database high similarity property during several different sub-database.Next,do the mapping according to the highest property.Using this mapping as the optimal path for querying, which realizes the purpose of distributed database queries.Finally, validation in experiment environment, this improved GLUE similarity algorithm can optimize distributed database query better, offer reference method for the design of the existing distributed database searching algorithm.