Semantic Integration of Information based on the Multi Aspect Semantic Model

In current multidatabase systems, an important problem is identifying semantic heterogeneities. The global schema multidatabases provide simple and effective paradigm; however creating and maintainging the global schema is difficult. Furthermore, these systems could not operate properly in dynamic environments. The new approaches using new technological developments such as agent technology, domain ontologies, intelligent mediator, and high-level query languages could operate properly in dynamic and open environments, but need well-established sharable knowledge which is a burdon to the user. In this paper, we suggest an approach for integrating information in multidatabase systems using Multi-Aspect Semantic Model(MASM). The MASM is a model which considers several aspects, such as semantic features, schematic aspect, neme, functional aspect, and context, to evalute the semantic similarity among objects and does not need well-established knowledge which must be acceptable among component databases. All necessary knowledge for integration is gathered independently in each component database rather than created and shared among component databases.