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OLA in the OAEI 2005 alignment contest

Abstract : Among the variety of alignment approaches (e.g., using machine learning, subsumption computation, formal concept analysis, etc.) similarity-based ones rely on a quantitative assessment of pair-wise likeness between entities. Our own alignment tool, OLA, features a similarity model rooted in principles such as: completeness on the ontology language features, weighting of different feature contributions and mutual influence between related ontology entities. The resulting similarities are recursively defined hence their values are calculated by a step-wise, fixed-point-bound approximation process. For the OAEI 2005 contest, OLA was provided with an additional mechanism for weight determination that increases the autonomy of the system.
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Submitted on : Wednesday, December 25, 2013 - 7:35:40 PM
Last modification on : Wednesday, February 2, 2022 - 3:58:01 PM
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  • HAL Id : hal-00922284, version 1



Jérôme Euzenat, Philippe Guégan, Petko Valtchev. OLA in the OAEI 2005 alignment contest. Proc. K-Cap 2005 workshop on Integrating ontology, Oct 2005, Banff, Canada. pp.97-102. ⟨hal-00922284⟩



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