On Applying Matching Tools to Large-scale Ontologies
نویسنده
چکیده
Many existing ontology matching tools are not well scalable. In this paper, we present the Malasco system, which serves as a framework for reusing existing, non-scalable matching systems on large-scale ontologies. The results achieved with different combinations of partitioning and matching tools are discussed, and optimization techniques are examined. It is shown that the loss of result quality when matching with partitioned data can be reduced to less than 5% compared to matching with unpartitioned data.
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تاریخ انتشار 2008