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Building ontology from scratch need identify the basic concepts, and their attributes and relationships. In terms of information integration, draft concepts, attributes and relationships can be directly captured by processing schemas of data sources. In this context, we present a hybrid semantic discovery approach, which is an extension of our previous work[1][2] to capture concepts, attributes and...
Building ontology from scratch need identify the basic concepts of application domain. In terms of database integration, draft concepts can be directly captured by processing schemas of databases. In this context, we present an automatic approach based on matching and clustering of relational schema columns to capture concepts from relative databases. By combining three individual name matchers following...
Although a lot of previous work on schema matching has developed many partial automatic matches for specific application domains, combining multiple match techniques enables achieving high accuracy for a large variety of match circumstances. In this context, we present a schema-based element matching approach that concatenates linguistic-based matchers and a constraint-based matcher. We propose a...
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