Abstract

In a distributed and open system, such as the semantic web and many other applications like information integration, peer- peer communication, etc., the heterogeneity among the data increases enormously. To solve the heterogeneity issue various matching techniques are proposed and large-scale matching needs especially to be supported for different kinds of ontologies and XML schemas due to their increasing use and size, e.g., in life science applications, e-business and web. In this paper the techniques which are scalable like early pruning, partitioning, parallelization and some renowned scalable matching techniques are discussed. In addition to it, a brief comparison of the discussed matching techniques is also presented.

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