Hybrid Approach for the Semantic Processing of Scientic Papers
Résumé
We propose a hybrid method for the extraction and characterization of citations in scientic papers using machine learning combined with rule-based approaches. Our protocol consists of the extraction of metadata, bibliography parsing, section titles processing, and nd-grained semantic annotation on the sentece level of texts. This allows us to generate Linked Open Data from a set of research papers in XML.
Origine : Fichiers produits par l'(les) auteur(s)
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