OLA in the OAEI 2005 Alignment Contest

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.

• Type: Conference
• Year: 2005
• Where: KCAP
• Authors: Jérôme Euzenat, Philippe Guégan, Petko Valtchev
• Keywords: Formal Concept Analysis, KCAP 2005, Ontology Language Features, Related Ontology Entities