Abstract:
Schema Matching can be efficiently done by
using ontology concepts. Ontology matching is one
of the well known topics of Semantic Web research.
With the development and the use of a huge variety
of data (e.g. DB schemas, ontologies, taxonomies),
in many domains (e.g. libraries, travelling, sports,
medical fields, etc), Matching Techniques are
attempted to overcome the challenge of reconciling
these different interrelated representations. In this
paper, we are interested in clustering web data
sources for large scale schema matching
approaches. We attempt to cover the problems of
some hidden regularities and semantic conflicts
over different representation of web databases. So,
we use a same model representation of ontologies to
tackle for all relational schemas for large scale
semantic matching in our system.
