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Reports (Research Report) Year : 2007

Mining Biomedical Texts to Generate Semantic Annotations


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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Dates and versions

inria-00125266 , version 1 (18-01-2007)
inria-00125266 , version 2 (22-01-2007)
inria-00125266 , version 3 (22-01-2007)


  • HAL Id : inria-00125266 , version 3


Khaled Mohamed 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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