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- W2167520007 abstract "In a distributed and open system, such as the semantic web and many other applications like information integration, peerpeer 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. General Terms Artificial Intelligence, Semantic Web, Knowledge sharing, Knowledge Representation." @default.
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- W2167520007 date "2011-11-29" @default.
- W2167520007 modified "2023-09-26" @default.
- W2167520007 title "A Comparative Analysis of Ontology and Schema Matching Systems" @default.
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