Manual schema matching is a problem for many database applications that use multiple data sources including data warehousing and e-commerce applications. Current research attempts to address this problem by developing algorithms to automate aspects of the schemamatching task. In this paper, an approach using an external dictionary facilitates automated discovery of the semantic meaning of datab...

We address the problem of unsupervised matching of schema information from a large number of data sources into the schema of a data warehouse. The matching process is the first step of a framework to integrate data feeds from thirdparty data providers into a structured-search engine’s data warehouse. Our experiments show that traditional schemabased and instance-based schema matching methods fa...

Current microarray databases use different terminologies and structures and thereby limit the sharing of data and collating of results between laboratories. Consequently, an effective integrated microarray data model is required. One important process to develop such an integrated database is schema matching. In this paper, we propose an effective schema matching approach called MDSM, to syntac...

A schema is an abstracted or a generalized knowledge to help with solving problems. A second-order predicate schema matching is a problem of computing the matchers of a pair 〈P, p〉 such that P is a second-order predicate schema and p is a first order closed formula. The second-order matching is known as NP-complete,in general. We propose a new matching algorithm based on the pre-checking of the...

With the development of the Linking Open Data (LOD) project, large amount of semantic datasets have been published on the Web. Due to the open and distributed nature of the Web, the published data may be heterogeneous both in the schema level and instance level. Matching the entities of different datasets is very important for integrating information from different data sources. Recently, much ...

In this paper we propose a method for automatic discovery of identity relationship Ley, M.: The DBLP Computer Science Bibliography: Evolution, Research Issues, Shvaiko, P., Euzenat, J.: A Survey of Schema-based Matching Approaches. Ontology-Based Method for Schema Matching in a Peer-to-Peer Database System. BNCOD Parallel query optimization methods and approaches: a survey. Guest Editors Ontolo...

Automating matching schemas has been under investigation in many areas for already some decades, but matching schemas is still often done manually by domain experts. Due to the rapidly increasing number of heterogeneous and distributed data sources in enterprises and on the web, the manual matching approach is more and more a limitation and the need for automating the schema matching process is...

We present XBenchMatch, a benchmark which uses as input the result of a schema matching algorithm (set of mappings and/or an integrated schema) and generates statistics about the quality of this input and the performance of the matching tool.

Schema matching is the task of finding semantic correspondences between elements of two schemas, which plays a key role in many database applications. In this paper, we cast the schema matching problem (SMP) into a multi-labeled graph matching problem. First, we propose an internal schema model: multi-labeled graph model, and transform schemas into multi-labeled graphs. Therefore, SMP reduce to...