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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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Contributor : Khaled Khelif Connect in order to contact the contributor
Submitted on : Monday, January 22, 2007 - 5:54:04 PM
Last modification on : Friday, February 4, 2022 - 3:19:14 AM
Long-term archiving on: : Wednesday, March 29, 2017 - 1:31:55 PM


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  • HAL Id : inria-00125266, version 3


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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