Making sense of massive amounts of scientific publications: the scientific knowledge miner project

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dc.contributor.author	Ronzano, Francesco
dc.contributor.author	Freire, Ana
dc.contributor.author	Sáez-Trumper, Diego
dc.contributor.author	Saggion, Horacio
dc.date	2016
dc.identifier.citation	Ronzano F, Freire A, Saez-Trumper D, Saggion H. Making sense of massive amounts of scientific publications: the scientific knowledge miner project. In: Cabanac G, Chandrasekaran MK, Frommholz I, Jaidka K, Kan M, Mayr P, Wolfram D, editors. Proceedings of the Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL); 2016 June 23; Newark, United States. [place unknown]: CEUR Workshop Proceedings; 2016. p. 36-41.
dc.identifier.citation	1613-0073
dc.identifier.uri	http://hdl.handle.net/10230/26969
dc.format	application/pdf
dc.language.iso	eng
dc.publisher	CEUR Workshop Proceedings
dc.relation	Cabanac G, Chandrasekaran MK, Frommholz I, Jaidka K, Kan M, Mayr P, Wolfram D, editors. Proceedings of the Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL); 2016 June 23; Newark, United States. [place unknown]: CEUR Workshop Proceedings; 2016. p. 36-41.
dc.relation	info:eu-repo/grantAgreement/EC/FP7/611383
dc.relation	info:eu-repo/grantAgreement/ES/1PE/TIN2015-65308-C5-5-R
dc.rights	Copyright © 2016 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	Text mining
dc.subject	Information extraction
dc.subject	Recommender systems
dc.subject	Indexing
dc.subject	Crawling
dc.subject	Online resources
dc.title	Making sense of massive amounts of scientific publications: the scientific knowledge miner project
dc.type	info:eu-repo/semantics/conferenceObject
dc.type	info:eu-repo/semantics/publishedVersion
dc.description.abstract	The World Wide Web has become the hugest repository ever for scientific publications and it continues to increase at an unprecedented rate. Nevertheless, this information overload makes the exploration of this content a very time-consuming task. In this landscape, the availability of text mining tools to characterize and explore distinctive features of the scientific literature is mandatory./nWe present the Scientific Knowledge Miner (SKM) Project, that aims to investigate new approaches and frameworks to facilitate the extraction of knowledge from scientific publications across different disciplines. More specifically, we will focus on citation characterization, recommendation and scientific document summarization.
dc.description.abstract	This work is supported by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502), by the European Project Dr. Inventor (FP7-ICT-2013.8.1 - Grant: 611383), the Catalonia Trade and Investment Agency (Agència per la competitivitat de l’empresa, ACCIÓ) and the TUNER project (TIN2015-65308-C5-5-R, MINECO/FEDER, UE).

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