Abstract
The problem of finding an agreement on the meaning of heterogeneous schemas is one of the key issues in the development of the Semantic Web. In this paper, we propose a new algorithm for discovering semantic mappings across hierarchical classifications based on a new approach to semantic coordination. This approach shifts the problem of semantic coordination from the problem of computing linguistic or structural similarities (what most other proposed approaches do) to the problem of deducing relations between sets of logical formulas that represent the meaning of nodes belonging to different schemas. We show how to apply the approach and the algorithm to an interesting family of schemas, namely hierarchical classifications. Finally, we argue why this is a significant improvement on previous approaches.
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Bouquet, P., Serafini, L., Zanobini, S. (2004). Coordinating Semantic Peers. In: Bussler, C., Fensel, D. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2004. Lecture Notes in Computer Science(), vol 3192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30106-6_8
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DOI: https://doi.org/10.1007/978-3-540-30106-6_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22959-9
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