Knowledge Enhanced Schema Matching for Heterogeneous Data Integration
Abstract
This dissertation systematically investigatesa knowledge-enhanced schema matching for heterogeneous data integration. The goal of this dissertation is to investigate the efficient way to learn and map high-quality knowledge bases from the existing relational data models and leverage them to enhance schema matching for heterogeneous data integration. This dissertation contributes to the semantic web community and database community by exploring the ontology learning framework, consistency checking method, text and knowledge enhancement schema matching for heterogeneous data integration.
Type
Publication
In Eötvös Loránd University
