We view match as an operator that takes two graph-like structures (e.g., classifications, XML schemas) and produces a mapping between the nodes of these graphs that correspond semantically to each other. Semantic matching is based on two ideas: (i) we discover mappings by computing semantic relations (e.g., equivalence, more general); (ii) we determine semantic relations by analyzing the meaning (concepts, not labels) which is codified in the elements and the structures of schemas. In this paper we present basic and optimized algorithms for semantic matching, and we discuss their implementation within the S-Match system. We evaluate S-Match against three state of the art matching systems, thereby justifying empirically the strength of our approach. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Giunchiglia, F., Yatskevich, M., & Shvaiko, P. (2007). Semantic matching: Algorithms and implementation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4601 LNCS, pp. 1–38). Springer Verlag. https://doi.org/10.1007/978-3-540-74987-5_1
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