Mining Biomedical Texts to Generate Semantic Annotations

Abstract : This report focuses on text mining in the biomedical domain for the generation of semantic annotations based on a formal model which is ontology. We start by exposing the generic methodology for the generation of annotations from texts. Then, we present a state of the art on different knowledge extraction techniques used on biomedical texts. We propose our approach based on Semantic Web Technologies and Natural Language Processing (NLP): it relies on formal ontologies to generate semantic annotations on scientific articles and on other knowledge sources (databases, experiment sheets). This approach can be extended to other do-mains requiring experiments and massive data analyses. Finally, we conclude with a discussion about our work and we present some learnt lessons.
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Rapport
[Research Report] RR-6102, INRIA. 2007, pp.25
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https://hal.inria.fr/inria-00125266
Contributeur : Khaled Khelif <>
Soumis le : lundi 22 janvier 2007 - 17:54:04
Dernière modification le : vendredi 12 janvier 2018 - 01:57:58
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  • HAL Id : inria-00125266, version 3

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Khaled Khelif, Rose Dieng-Kuntz, Pascal Barbry. Mining Biomedical Texts to Generate Semantic Annotations. [Research Report] RR-6102, INRIA. 2007, pp.25. 〈inria-00125266v3〉

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