BMatch: a Semantically Context-based Tool Enhanced by an Indexing Structure to Accelerate Schema Matching

Schema matching is a crucial task to gather information of the same domain. This is more true on the web, where a large number of data sources are available and require to be matched. However, the schema matching process is still largely performed manually or semi-automatically, discouraging the deployment of large-scale mediation systems. Indeed, these large-scale scenarii need a solution which ensures both an acceptable matching quality and good performance. In this article, we present an approach to match efficiently a large number of schemas. The quality aspect is based on the combination of terminological methods and cosine measure between context vectors. The performance aspect re∗Supported by ANR Research Grant ANR-05-MMSA0007 lies on a B-tree indexing structure to reduce the search space. Finally, our approach, BMatch, has been implemented and the experiments with real sets of schemas show that it is both scalable and provides an acceptable matching quality when compared with the results obtained by the most referenced matching tools.

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