Schema matching, which tries to find semantic correspondences between schema elements, is a key operation in data engineering. Combining multiple matching strategies is a very promising technique for schema matching. To overcome the limitations of existing combination systems and to achieve better performances, in this paper the CMC system is proposed, which combines multiple matchers based on ...

One of the key challenges in the development of open semantic-based systems is enabling the exchange of meaningful information across applications which may use autonomously developed schemata. One of the typical solutions for that problem is the definition of a mapping between pairs of schemas, namely a set of point–to–point relations between the elements of different schemas. A lot of (semi-)...

The World-Wide Web Consortium (W3C) promotes XML and related standards, including XML Schema, XQuery, and XPath. This paper describes a formalization XML Schema. A formal semantics based on these ideas is part of the official XQuery and XPath specification, one of the first uses of formal methods by a standards body. XML Schema features both named and structural types, with structure based on t...

Schema matching is a fundamental issue in 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, instancebased or semantic, is to detect how the same real world objects are represented in different database...

An ontology typically provides a vocabulary that describes a domain of interest and a specification of the meaning of terms used in the vocabulary. Depending on the precision of this specification, the notion of ontology encompasses several data and conceptual models, for example, classifications, database schemas, fully axiomatized theories. Ontologies tend to be put everywhere. They are viewe...

Semantic matching of schemas in heterogeneous data sharing systems is time consuming and error prone. Existing mapping tools employ semi-automatic techniques for mapping two schemas at a time. In a large-scale scenario, where data sharing involves a large number of data sources, such techniques are not suitable. In this paper we present a method, which creates a mediated schema tree from a larg...

We address the problem of matching imperfectly documented schemas of data streams and large databases. Instance-level schema matching algorithms identify likely correspondences between attributes by quantifying the similarity of their corresponding values. However, exact calculation of these similarities requires processing of all database records—which is infeasible for data streams. We devise...

We propose a flexible framework called MOMA for mapping-based object Object matching or object consolidation is a crucial task for data integration and 370, COMA A System for Flexible Combination of Schema Matching Approaches. Schema matching and mapping are an important tasks for many applications, such as data integration, data warehousing and e-commerce. First and foremost our approach is ba...

Discovering correspondences between schema elements is a crucial task for data integration. Most schema matching tools are semiautomatic, e.g., an expert must tune certain parameters (thresholds, weights, etc.). They mainly use aggregation methods to combine similarity measures. The tuning of a matcher, especially for its aggregation function, has a strong impact on the matching quality of the ...