Schema Evolution publication categorizer

Schema matching is a fundamental issue to many
database applications, such as query mediation and data
warehousing. It becomes a challenge when different vocabularies
are used to refer to the same real-world concepts. In
this context, a convenient approach, sometimes called extensional,
instance-based, or semantic, is to detect how the
same real world objects are represented in different databases
and to use the information thus obtained to match the
schemas. Additionally, we argue that automatic approaches
of schema matching should store provenance data about
matchings. This paper describes an instance-based schema
matching technique for an OWL dialect and proposes a data
model for storing provenance data. The matching technique
is based on similarity functions and is backed up by experimental
results with real data downloaded from data sources
found on the Web.