Knowledge extraction and modeling from scientific publications

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• dc.contributor.author Ronzano, Francescoca
• dc.contributor.author Saggion, Horacioca
• dc.date.accessioned 2018-01-30T08:40:29Z
• dc.date.available 2018-01-30T08:40:29Z
• dc.date.issued 2016
• dc.description Comunicació presentada al International Workshop on Semantic, Analytics, Visualization (SAVE-SD 2016), celebrat el dia 11 d'abril de 2016 a Montreal, Canadà.
• dc.description.abstract During the last decade the amount of scientific articles available online has substantially grown in parallel with the adoption of the Open Access publishing model. Nowadays researchers, as well as any other interested actor, are often overwhelmed by the enormous and continuously growing amount of publications to consider in order to perform any complete and careful assessment of scientific literature. As a consequence, new methodologies and automated tools to ease the extraction, semantic representation and browsing of information from papers are necessary. We propose a platform to automatically extract, enrich and characterize several structural and semantic aspects of scientific publications, representing them as RDF datasets. We analyze papers by relying on the scientific Text Mining Framework developed in the context of the European Project Dr. Inventor. We evaluate how the Framework supports two core scientific text analysis tasks: rhetorical sentence classification and extractive text summarization. To ease the exploration of the distinct facets of scientific knowledge extracted by our platform, we present a set of tailored Web visualizations. We provide on-line access to both the RDF datasets and the Web visualizations generated by mining the papers of the 2015 ACL-IJCNLP Conference.en
• dc.description.sponsorship This work is (partly) supported by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502) and by the European Project Dr. Inventor (FP7-ICT-2013.8.1 - Grant no: 611383).
• dc.format.mimetype application/pdf
• dc.identifier.citation Ronzano F, Saggion H. Knowledge extraction and modeling from scientific publications. In: González-Beltrán A, Osborne F, Peroni S, editors. Semantics, Analytics, Visualization. Enhancing Scholarly Data. Second International Workshop, SAVE-SD 2016; 2016 Apr 11; Montreal, Canada. Cham (Switzerland): Springer; 2016. pp. 11-25. DOI: 10.1007/978-3-319-53637-8_2
• dc.identifier.doi http://dx.doi.org/10.1007/978-3-319-53637-8_2
• dc.identifier.uri http://hdl.handle.net/10230/33775
• dc.language.iso eng
• dc.publisher Springerca
• dc.relation.ispartof González-Beltrán A, Osborne F, Peroni S, editors. Semantics, Analytics, Visualization. Enhancing Scholarly Data. Second International Workshop, SAVE-SD 2016; 2016 Apr 11; Montreal, Canada. Cham (Switzerland): Springer; 2016. pp. 11-25.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/611383
• dc.rights © Springer The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-53637-8_2
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Scientific knowledge extractionen
• dc.subject.keyword Knowledge modelingen
• dc.subject.keyword RDFen
• dc.subject.keyword Software frameworken
• dc.title Knowledge extraction and modeling from scientific publicationsca
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion