MultiScien: a bi-lingual natural language processing system for mining and enrichment of scientific collections

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To access the full text documents, please follow this link: http://hdl.handle.net/10230/32537

dc.contributor.author	Saggion, Horacio
dc.contributor.author	Ronzano, Francesco
dc.contributor.author	Accuosto, Pablo
dc.contributor.author	Ferrés, Daniel
dc.date	2017
dc.identifier.citation	Saggion H, Ronzano F, Accuosto P, Ferrés D. MultiScien: a bi-lingual natural language processing system for mining and enrichment of scientific collections. In: Mayr P, Chandrasekaran MK, Jaidka K, editors. Proceedings of the 2nd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2017); 2017 Aug 11; Tokyo, Japan. [place unknown]: CEUR Workshop Proceedings; 2017. p. 26-40.
dc.identifier.uri	http://hdl.handle.net/10230/32537
dc.format	application/pdf
dc.language.iso	eng
dc.publisher	CEUR Workshop Proceedings
dc.relation	Mayr P, Chandrasekaran MK, Jaidka K, editors. Proceedings of the 2nd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2017); 2017 Aug 11; Tokyo, Japan. [place unknown]: CEUR Workshop Proceedings; 2017. p. 26-40.
dc.relation	info:eu-repo/grantAgreement/ES/1PE/TIN2015-65308-C5-5-R
dc.rights	© 2017 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors.
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Language Resources
dc.subject	Scientific Text Corpora
dc.subject	Information Extraction
dc.subject	Data Visualization
dc.subject	Semantic Analysis
dc.subject	PDF Conversion
dc.title	MultiScien: a bi-lingual natural language processing system for mining and enrichment of scientific collections
dc.type	info:eu-repo/semantics/conferenceObject
dc.type	info:eu-repo/semantics/acceptedVersion
dc.description.abstract	Comunicació presentada a: 2nd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2017) celebrada a Tokyo l'11 d'agost de 2017.
dc.description.abstract	In the current online Open Science context, scientific datasets and tools for deep text analysis, visualization and exploitation play a major role.We present a system for deep analysis and annotation of scientific text collections. We also introduce the first version of the SEPLN Anthology, a bi-lingual (Spanish and English) fully annotated text resource in the field of natural language processing that we created with our system. Moreover, a faceted-search and visualization system to explore the created resource is introduced. All resources created for this paper will be available to the research community.
dc.description.abstract	This work is (partly) supported by the Spanish Ministry of Economy and Com- petitiveness under the Maria de Maeztu Units of Excellence Programme (MDM- 2015-0502) and by the TUNER project (TIN2015-65308-C5-5-R, MINECO/FEDER, UE).

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