A context-based approach for the discovery of complex matches between database sources

Abstract

The elaboration of semantic matching between hetero geneous data sources is a fundamental step in the design of data sharing applications. This task is tedious and often error prone if handled manually. Therefore, many systems have been developed for its automation. But, the majority of them focus on the problem of finding simple (one-to-one) matching. This is likely due to the fact that complex (many-to-many) matching raises a far more difficult problem since the search space of concept combinations can be tremendously large. This article presents INDIGO, a system which can compute complex matching by taking into account data sources' context. First, it enriches data sources with complex concepts extracted from their respective development artifacts. It then computes a mapping between the two data sources thus enhanced. © Springer-Verlag Berlin Heidelberg 2007.