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Approximate structure-preserving semantic matching

by Fausto Giunchiglia, Fiona McNeill, Mikalai Yatskevich, Juan Pane, Paolo Besana, Pavel Shvaiko
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ()


Typical ontology matching applications, such as ontology integration, focus on the computation of correspondences holding between the nodes of two graph-like structures, e.g., between concepts in two ontologies. However, for applications such as web service integration, we need to establish whether full graph structures correspond to one another globally, preserving certain structural properties of the graphs being considered. The goal of this paper is to provide a new matching operation, called structure-preserving semantic matching. This operation takes two graph-like structures and produces a set of correspondences, (i) still preserving a set of structural properties of the graphs being matched, (ii) only in the case if the graphs are globally similar to one another. Our approach is based on a formal theory of abstraction and on a tree edit distance measure. We have evaluated our solution in various settings. Empirical results show the efficiency and effectiveness of our approach.

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