Extraction and Characterization of Citations in Scientific Papers

Abstract : We propose a hybrid method for the extraction and characterization of citations in scientific papers using machine learning combined with rule-based approaches. Our protocol consists of the extraction of metadata, bibliography parsing, section titles processing, and find-grained semantic annotation on the sentence level of texts. This allows us to generate Linked Open Data from a set of research papers in XML.
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https://hal.archives-ouvertes.fr/hal-01941180
Contributor : Marc Bertin <>
Submitted on : Friday, November 30, 2018 - 5:43:53 PM
Last modification on : Wednesday, August 14, 2019 - 2:18:05 PM

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Marc Bertin, Iana Atanassova. Extraction and Characterization of Citations in Scientific Papers. Presutti V. et al. Semantic Web Evaluation Challenge. SemWebEval 2014., 475, ⟨Springer⟩, pp.120-126, 2014, Semantic Web Evaluation Challenge. SemWebEval 2014. Communications in Computer and Information Science, 978-3-319-12023-2. ⟨10.1007/978-3-319-12024-9_16⟩. ⟨hal-01941180⟩

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