Semantic similarity between controled vocabularies

Semantic similarity between controled vocabularies

Mélissa Mary Lina F. Soualmia Xavier Gansel

bioMérieux SA, Département développement et intégration, 3 route de Port Michaud, 38390 La Balme Les Grottes, France

LITIS EA 4108 et NormaSTIC CNRS 3638, Normandie Université, Université de Rouen de Normandie, 76000 Rouen, France

LIMICS INSERM UMR_1142, Sorbonne Universités, 75000 Paris, France

Corresponding Author Email: 
{melissa.mary, xavier.gansel},
31 December 2016
| Citation



Medical data numerization raises syntactic but also semantic interoperability challenges between information systems and knowledge organisation systems. Knowledge integration was largely studied into general purposes as in specific domain such as clinical and biology. As in vitro diagnostics is transdisciplinary domain it should answer to the same knowledge integration issues, which are encountered in clinical and biological field, using tools adapted to its multidisciplinary knowledge. In this article we propose a literature review about knowledge integration and linked data state of art with a specific focused on IVD data. We present an evaluation of concepts alignment extracted from two standards used in DIV and available on line. Methods we propose are based on three lexical semantic similarity measures and one heuristic algorithm. Results we obtained illustrates that lexical measures are not enough efficient to be used into laboratory domain. However, alignments obtained with the heuristic approach and filtered with a semantic dimension comply with our performance criteria. This strategy is under improvement process by the integration of semantic similarity and the refinement of lexical parameter into the heuristic approach.


data integration, ontology alignment, biomedical terminology

1. Introduction
2. Revue de littérature
3. Matériel et méthode
4. Résultats et discussion
5. Conclusion

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