Ontology-based top-k global schema generation


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A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science
Global schema generation is the problem of generating a unified schema based on existing heterogeneous local schemas and a set of correspondences which are generated by a schema matching algorithm. The current schema integration approaches cannot satisfy users' requirements due to several reasons. The existing approaches cannot handle hierarchical schema structure, cannot solve conflicts problems, and only generates one merging result. To deal with these kinds of problems, top-k global schema generation approach is proposed in this research. The proposed approach consists of three steps: (1) Relational schemas are converted to ontologies; (2) Ontologies are merged and top-k results are generated; (3) Users can choose one of the top-k merged ontologies and convert it back to the relational schema. The approach utilizes ontology as a base merging model to create the global schema, because ontology can provide semantic and detail constraints. The objective of this research is to generate the global schema with high quality but less user involvement. Since different users may have their own preferred global schemas, top-k ranking algorithms are utilized to obtain multiple schema integration results, so users may have more than one choice. After comparing the approach in this research with state of the art schema integration approaches, the proposed approach better preserves the hierarchical structure, and generates the global schema with higher quality.
Computing Sciences
College of Science and Engineering